The Dynamic Interplay Between Digitalization and Human Capital Development in Vietnam (1996-2019)

The study investigates the dynamic relationships between digitalization and the development of human capital in Vietnam from 1996 to 2019. Vietnam has implemented numerous policies to advance human knowledge and the digital transformation process, often using incentive-based approaches to encourage firms to adopt digital technologies across functions such as sales and customer service. Understanding how digital innovation affects the economy, society, environment, and human capital—along with knowledge spillovers—is crucial for effective policymaking. The paper positions itself as the first to examine how digital transformation adoption in Vietnam necessitates changes in human capital performance, particularly salient after COVID-19. Given limited data availability in Vietnam, the authors employ novel econometric techniques to provide new statistical insights and inform policy and human resource development in the digital age.

The paper outlines the evolution of human capital theory from classical economists (e.g., Smith, Say, Petty) to neoclassical contributions (Becker, Schultz, Mincer), emphasizing education, training, and health as investments that enhance productivity and drive economic growth. It highlights challenges in measuring human capital due to its multidimensional and dynamic nature. Assessments can be conducted at micro (individual, firms), meso (industries/regions), macro (national), and mega (global) levels. Common evaluation approaches include: (1) investment-based methods (costs of education, training, and health that enhance productivity), (2) return-based methods (benefits of investments), and (3) indicator-based methods (skills, competencies, literacy). Each has limitations, but combined approaches offer adaptability. The review motivates examining the interlink between digitalization and human capital by noting how capabilities and knowledge accumulation affect production processes and, consequently, the uptake and outcomes of digital transformation.

Data consist of Vietnam’s annual time series from 1996 to 2019 for indicators including internet users (INU), mobile subscribers (MOBSUB), CO2 emissions, and the human capital index (HCI). Exploratory plots of first log-differences show notable pre-2003 fluctuations in INU and MOBSUB, contemporaneous volatility in GDP and CO2, and a steady rise in HCI. The empirical strategy applies a time-varying parameter vector autoregression with an extended joint connectedness framework (TVPVAR-EJC), building on Diebold and Yilmaz (2012). Lag length is chosen via the Bayesian Information Criterion. The TVP-VAR is recast into a time-varying VMA to compute generalized forecast error variance decompositions (GFEVD) that are not contingent on orthogonalized shocks, allowing time-varying covariances. From GFEVD, the study derives directional connectedness measures: total “from” and “to” spillovers for each indicator, net total directional connectedness (to minus from), the total connectedness index (TCI), and net pairwise spillovers. To address scaling and ensure row sums and diagonals meet joint connectedness requirements, the method incorporates the joint spillover index approach (Lastrapes and Wiesen, 2021) with row-specific scaling factors, producing a joint connectedness table that preserves time variation and comparability across indicators. This framework enables identification of net transmitters and receivers of shocks among digitalization, human capital, and environmental-economic variables under limited data conditions.

Descriptive evidence indicates substantial pre-2003 volatility in digital adoption measures (internet users and mobile subscribers), consistent with major Vietnamese policy initiatives (infrastructure development, administrative reforms, tax incentives, and digital transformation efforts). Over the sample, GDP volatility mirrors CO2 emissions dynamics, while the human capital index trends upward steadily. Detailed connectedness results (e.g., net transmitters/receivers, TCI magnitudes) are not included in the provided excerpt.

The connectedness-based evidence and the proposed framework aim to inform both short- and long-term decision-making regarding digital transformation and human resource development. By clarifying dynamic linkages and shock transmission between digitalization, human capital, and related economic-environmental indicators, the study provides actionable insights for policymakers to design incentive-compatible policies that enhance knowledge spillovers and human capital outcomes, while anticipating unintended consequences of digital policy interventions.

The study contributes by (1) being, to the authors’ knowledge, the first to analyze how digital transformation in Vietnam interacts with and requires changes in human capital performance; (2) employing an innovative TVPVAR-EJC connectedness approach suitable for data-scarce contexts; and (3) offering policy-relevant insights for advancing the digital economy and human resource development. The framework can guide policymakers in structuring incentives and support mechanisms that foster digital innovation and human capital enhancement. Future research could extend the indicator set, incorporate sectoral granularity, and evaluate post-COVID dynamics as more data become available.

Limited data availability in Vietnam constrains traditional empirical approaches and the breadth of indicators that can be included. While the TVPVAR-EJC framework mitigates some issues, results may still be sensitive to variable selection, sample period, and time-varying assumptions about variances and covariances.