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While existing literature acknowledges the development of digital capabilities as essential for enterprises to achieve digital transformation, it falls short in offering comprehensive theoretical insights into the dynamic evolution of these capabilities, especially in the field of environmental and sustainability issues. This paper addresses this gap by employing an exploratory single-case study methodology to investigate the intricate process through which an ecological restoration enterprise in China updates its digital strategy, facilitating the dynamic evolution of its digital capabilities from a resource orchestration theory perspective. Our findings reveal a sequential evolution from digital strategy renewal to resource orchestration and, ultimately, the advancement of digital capabilities. Specifically, the enterprise engages in a co-adjustment and co-creation process, aligning its resources with a digital strategy refresh and fostering the emergence of digital integration and innovation capabilities through effective resource management. This includes the accumulation and divesting of resources as part of the construction process, alongside the enrichment and bundling of resources. This research bridges the gap in the current literature by providing a nuanced understanding of the mechanisms that drive the evolution of digital capabilities, and it offers a theoretical framework that integrates strategic renewal with resource orchestration for environmental and socio-economic sustainable development. Furthermore, the insights gained provide vital managerial implications for the governance, corporate social responsibility and policy of industrial digitalization towards global environmental practice and sustainable development goals (SDGs). [ABSTRACT FROM AUTHOR]

As the path of industrial eco-efficiency (IEE) needs to be re-examined from a multi-dimensional perspective, this research opens the internal "black box" of China's industrial eco-economic system driven by sustainable development goals (SDGs) and decomposes IEE into industrial production and sustainable development stages. It further divides the industrial production stage into two parallel subsystems of water use efficiency (WUE) and energy efficiency (EE) and derives SDG6 efficiency (SDG 6 E) and SDG7 efficiency (SDG 7 E) in the sustainable development stage respectively. The paper proposes a meta two-stage parallel entropy dynamic DDF-DEA model to re-measure IEE of 30 provinces in China from 2015 to 2021, discusses the relationship between overall efficiency and stage efficiency, and by using the Tobit model explores various types of influencing factors by subregion. The results show that the modified DDF-DEA model can explore China's IEE more accurately under SDGs. China's IEE is more stable from 2015 to 2021, with the efficiency value always fluctuating between 0.59 and 0.64, the overall level is low, and there is more room for improvement. There are significant inter-provincial differences in IEE and efficiency inertia. In more than 75% of the provinces SDG 7 E constrains IEE improvement, while the dynamic evolution of IEE and its subsystem efficiency varies across regions. Environmental regulation is a common factor affecting IEE across the country and in the east, central, and west regions, whereas the level of economic development, openness to the outside world, and urbanization rate are differential factors affecting IEE across the country and in the three major regions. This study offers new perspectives for exploring the path of IEE enhancement and providing empirical references for the collaborative construction of industrial ecological civilization. [Display omitted] [ABSTRACT FROM AUTHOR]