“Digitalisation” and “Greening” as Components of Technology Upgrading and Sustainable Economic Performance

Abstract

This paper explores the pace and direction of technological development by using a technology upgrade conceptual and measurement framework. This approach is applied to a sample of 164 economies worldwide between 2002 and 2019. Within the framework of technology upgrading, the paper focuses on digitalisation and “greening” as its two significant structural features. We explore their relationship with different components of technology upgrading and the relationship between technology upgrading components and different indicators of macroeconomic productivity. We have adopted a longitudinal fixed effects regression method with control for unobserved heterogeneity, clustered standard errors, and time dummies. Our results show that the growth of research and development (R&D) capabilities does not translate into aggregate productivity growth. There is a lack of unconditional relationship between aggregate productivity growth, digitalisation and greening. However, there are “latecomer advantages” to basic digitalisation for lower middle- and low-income economies and “latecomer liabilities” in the greening of the economy for upper-middle-income economies. In addition, levels of digitalisation and greening do not correlate, suggesting these two transformation processes are not yet integrated into ‘ICT-assisted greening’. When we control for income levels, the impact of components of technology upgrading on productivity is isolated to specific components and significant only for some income groups. The absence of a significant simultaneous effects of several components of technology upgrading on productivity points to large transformation failures. We conclude that the role of science and technology systems in spurring sustainable development would require a broad scope for science and technology (S&T) policies, their coordination, and integration with non-innovation policies.

Progress in Sustainable Recycling and Circular Economy of Tungsten Carbide Hard Metal Scraps for Industry 5.0 and Onwards

“…The diverse chemical and physical composition of WC scrap requires the adoption of various recycling techniques to ensure the recovery of substantial quantities of WC with exceptional purity. Several direct (mechanical), indirect (chemical), and [38,74,76,81,82,127,134,137,146,158,[161][162][163][164]174,175,178,183,184]. [38,74,76,81,82,127,134,137,146,158,[161][162][163][164]174,175,178,183,184].…”

“…The 'smart and green' Industry 6.0 is expected to drive the future by intelligent data collection and sorting (cloud computing) [174], proactive decision making [141], omni-channel interactions [186], hyperconnected business environments [187], and smart renewable energy sources integration [76]. technologies, policy structure, circularity, and green technologies [38,74,76,81,82,127,134,137,146,158,[161][162][163][164]174,175,178,183,184]. [141,142,146,148,173,181,184,186,187].…”

A Study on the Impact Mechanism of Digitalization on Corporate Green Innovation

“…Secondly, the improvement of enterprise digitalization level is conducive to reducing the cost of green innovation of enterprises. Firstly, the higher the degree of digital transformation of enterprises, the more timely the application of digital technology makes the information transmission and processing, and the cost of enterprises to obtain and screen effective R & D information is lower [70]. Second, enterprise digitalization can rapidly enhance the quality of innovative talents through learning effect and replacement effect [71] to match the quality of innovative talents with innovative technologies, reduce the cost of knowledge accumulation of innovative talents, improve the efficiency of innovation, and enhance the R & D capability of enterprises.…”

Cognitions affecting innovation among generation Z entrepreneurs: the external enablement of digital infrastructure

“…We argue that this enablement role entails knowledge acquisition, assimilation and transformation mechanisms that can shape or change the entrepreneurs' mental models and, thus, change the resource acquisition, allocation and integration toward innovation. DI can facilitate the acquisition of knowledge about market needs and potential market trends through search possibilities (Forman and Van Zeebroeck, 2019;Yin and Yu, 2022), assimilating it through social media communications or open-source innovation communities (Zhang and Hon, 2020;Zhang et al, 2014) and transforming it to a new knowledge toward innovation by increasing complementarities (Bruno et al, 2023;Zakaryan, 2023). These knowledge-related mechanisms enabled by DIs can improve the acquisition of substitutive or primary resources and raw materials through search possibilities (Appio et al, 2021;Savino et al, 2017).…”

“…They can also enhance resource allocation by compressing the time and resources necessary for innovation, leading entrepreneurs to experiment with new ideas faster and with lower operational costs (Kallinikos et al, 2013). Finally, they help combine and integrate different resources for creating new products and services through complementarities (Bruno et al, 2023;Zakaryan, 2023). Hence, the digital infrastructure's knowledge acquisition, assimilation and transformation mechanisms can enable the cognitive processes of innovation.…”