Ali Ahsan

This research is focused on knowledge-based performance drivers, which are often intertwined with intellectual capital (IC); specifically, the value-added intellectual coefficient (VAIC) and its profound influence on labor productivity (LP), with the pivotal inputs of training and research and development (R&D) as moderating, in the realm of small- and medium-sized (engineering) enterprises (SMEs). The aim is to offer this as a sustainable model for practical implementation to empower engineering managers, donors, and policy researchers. The motivation catalyzes more informed decision-making investing in human or structural capital. It attempts to foster sustainable growth and societal stability through job creation within the knowledge-intensive engineering sector of developing countries. Methodologically, the research draws upon statistical analysis, employing Pearson’s correlation, multivariate regression, and model testing executed through specialized statistical software. The World Bank Enterprise Survey Instrument was used to collect data on 213 aviation-related firms. Primary data were collected for the years 2013–2022. Several hypotheses were developed between the variables expected to relate positively, because intellectual capital, training, and research and development should lead to better labor productivity. The findings revealed the critical issue of the misallocated investments in structural capital that this model brought forth. Furthermore, the notable contribution to national intellectual capital (NIC) studies is the significant VAIC value of 4.58 and an impressive labor productivity value of 6.78 within the knowledge-intensive ecosystem of SMEs. More insightful findings were the modest 17% positive variation attributable to the VAIC on LP, accompanied by an absence of significant influence exerted by training and R&D on this relationship. While underscoring the model’s overall validity, this intriguing discovery emphasizes the impact of intangibles on knowledge firms’ overall sustainability calculations, specifically structural capital, which accounts for a substantial 31% of labor productivity. The practical implication is that this model can be used to expose long-term financial performance hiccups through intellectual capital measures. The novelty is employing the labor productivity metric sourced from the engineering literature instead of the customary asset productivity (ATO) ratio from the IC literature.