Conference Agenda

The importance of innovation ecosystems and technology upgrading are emphasised in the catch-up literature. Yet, there is limited evidence-based understanding of the interaction between technological upgrades and innovation ecosystems in contexts where there are persistent weaknesses in technology upgrading and low investment in research and development (R&D). Using pooled data from the two waves of 2007 and 2020 of the World Bank’s Enterprise Survey (WBES), this paper constructs novel multidimensional indicators of technological upgrades and innovation ecosystems. Estimating structural models, the paper examines the effect (direct and indirect) of the self-constructed technology upgrading and innovation ecosystem indices on the performance of productivity and export of South African firms. The findings show a positive complementary effect of technology upgrading and innovation ecosystems on labour productivity. On the contrary, the results suggest that technology upgrading and innovation ecosystems matter differently for export performance. The findings have implications for innovation policy and for firm-level strategies for innovation and technology upgrading towards enhanced performance.

Abstract

Purpose

This study was carried out to examine the effect of human capital development, innovation, and industrial sector performance in Sub-Saharan African (SSA) countries. The main objective of this study is to determine the interactive effect of both human capital development and innovation on industrial sector performance in SSA countries.

Design/Methodology/Approach

Using data from World Bank Indicators, UNDP's Human Development Index (HDI), and the Global Innovation Index spanning 2011-2021, the research employs the system generalized method of moments (SYS GMM) for analysis. This study applies the integrated framework of Kaldor’s Manufacturing theory, Schumpeter’s theory and human capital theory.

Findings

The result shows that the interactive effect of HCD and Innovation leads to positive and significant effect on industrial sector performance in SSA. The findings highlight the tangible impact of human capital on industrial performance, stressing the value of skilled individuals in boosting competitiveness in manufacturing. Moreover, the study underscores the pivotal role of innovation, demonstrated by its positive influence on the industrial sector. Although educational investment shows a positive albeit statistically insignificant effect on industrial performance, it suggests potential long-term benefits for the sector.

Originality/Value

Previous studies have not adequately explored the tripartite relationship amongst Human Capital Development Innovation and Industrial sector performance in SSA region. This paper considered a robust Industrial Sector Performance theory rather than just focusing on Economic Growth Models.

Abstract

In today's digital era, manufacturing firms face increasing pressure to innovate and adapt their business models to keep pace with rapid digitization and a dynamic market landscape. This research investigates the key enablers of business model innovation (BMI) within Ethiopian manufacturing firms. To address the research objectives, Data was collected from a pool of 164 manufacturing firms in Ethiopia. The participants were conveniently selected based on their relevance to the study. The study used Partial Least Squares-Structural Equation Modeling (PLS-SEM) to analyze the effects of enabler variables on business model innovation. The research findings showed positive relationships between BMI and variables like Innovation Capability (IC), Digital Capability (DigC), Dynamic Capability (DC), Business Environment (BE), and Strategic Agility (SA). However, only DC, DigC, and BE were significant antecedents of BMI, with DC having the greatest influence in the case firms. These findings provide insights into the driving factors of BMI. The study contributes to the existing knowledge on BMI and offers valuable insights for practitioners in the manufacturing sector. However, the study has limitations, including a focus solely on the manufacturing sector and only six variables. Future research should expand the variable size and consider other sectors for broader insights.