Chunxiao Huang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Chunxiao Huang has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Dan Zhao
Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China
1 shared publication - Keming Chen
Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
1 shared publication - Tianqi Zhu
Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
1 shared publication - Ting Wang
Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
1 shared publication - Tingting Li
Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
1 shared publication
Latest Publications
- Open Access
An Adaptive Lag Trap in Socio-Technical Systems: The Paradoxical Effect of Digitalization and Labor on Logistics Investment in China
The economic efficacy of logistics infrastructure is being reshaped by the dual forces of digitalization and the labor market. However, a new-era “investment return paradox” has emerged. Digitalization and an abundant labor force are theoretically positive forces, so why does their combination, when coupled with capital investment, paradoxically engender negative emergence that suppresses growth? Conceptualizing the regional economy as a Socio-Technical System (STS), this paper unravels this paradox by identifying and theorizing an “adaptive lag trap”. Using provincial panel data from China, we first provide empirical validation for this trap, identifying a significant negative three-way interaction involving labor quantity (coef. = −0.218, p < 0.05). We then demonstrate that high-skilled labor quality is the key to mitigating this trap. While its direct interactive effects are not statistically significant, our analysis uncovers a robust and theoretically potent pattern: a higher-skilled workforce systematically reverses the negative trend of the interaction effect. The split-sample test provides the clearest evidence of this pattern, showing the coefficient pivoting from negative (−0.0572) in the low-skill subsample to positive (+0.109) in its high-skill counterpart. Our findings establish that high-skill human capital is a necessary condition to circumvent the “adaptive lag trap”, underscoring the imperative for a policy shift from investing in the scale of labor to cultivating its skill structure within a co-evolutionary framework.
Open AccessAn Adaptive Lag Trap in Socio-Technical Systems: The Paradoxical Effect of Digitalization and Labor on Logistics Investment in China
The economic efficacy of logistics infrastructure is being reshaped by the dual forces of digitalization and the labor market. However, a new-era “investment return paradox” has emerged. Digitalization and an abundant labor force are theoretically positive forces, so why does their combination, when coupled with capital investment, paradoxically engender negative emergence that suppresses growth? Conceptualizing the regional economy as a Socio-Technical System (STS), this paper unravels this paradox by identifying and theorizing an “adaptive lag trap”. Using provincial panel data from China, we first provide empirical validation for this trap, identifying a significant negative three-way interaction involving labor quantity (coef. = −0.218, p < 0.05). We then demonstrate that high-skilled labor quality is the key to mitigating this trap. While its direct interactive effects are not statistically significant, our analysis uncovers a robust and theoretically potent pattern: a higher-skilled workforce systematically reverses the negative trend of the interaction effect. The split-sample test provides the clearest evidence of this pattern, showing the coefficient pivoting from negative (−0.0572) in the low-skill subsample to positive (+0.109) in its high-skill counterpart. Our findings establish that high-skill human capital is a necessary condition to circumvent the “adaptive lag trap”, underscoring the imperative for a policy shift from investing in the scale of labor to cultivating its skill structure within a co-evolutionary framework.