Green technology innovation (GTI) capability plays an important role in realizing the sustainable development of intelligent manufacturing (IM) industry. Extensive research has addressed the evaluation of GTI capability. However, existing evaluation models primarily include either qualitative or quantitative indexes. Rarely do they integrate both types of indexes simultaneously. To address this gap, we establish two types of GTI capability evaluation index system from the perspective of core competitiveness. Then, we propose the concept of the interval linguistic Z-number vector (ILZNV) based on the Z-number to represent n-dimensional uncertain information of GTI capability evaluation. Subsequently, theories regarding ILZNVs, including normalization, operational rules, comparison method and distance measure, are discussed. We also propose a method for unifying both types of index data by converting numerical values to ILZNVs. After determining decision makers' (DMs') combined weights and attribute weights, a multi-attribute group decision making (MAGDM) model is developed using operators and the MULTIMOORA method of ILZNVs. The model is then applied to evaluate the GTI capability of IM enterprises. Comparative analysis demonstrates the effectiveness and superiority of the proposed method. Finally, we present several managerial and theoretical implications.

The green transformation of heavily polluting companies is essential for sustainable development. This study investigated the direct effects of environmental regulation on two types of green technology innovations at the microlevel and explored the moderating effects of three levels of firm supervision—government, public, and internal. Analyzing a panel of China’s heavily polluting companies during 2011–2020, we find that environmental regulation inhibits both types of green technology innovation. However, the degree of such inhibition varies with different moderators. Specifically, lower environmental pressure and better internal corporate controls can weaken or even reverse the inhibition of green invention innovation, while higher media attention can weaken the inhibition of green utility-model innovation. Our findings thus extend the literature on the scenarios of environmental regulation by revealing the heterogeneous moderating effects of government-, public-, and firm-level factors on two types of green innovation. Moreover, our findings have practical implications for promoting the green transformation of heavily polluting companies.

Based on the panel data of 30 provinces in China from 2013 to 2022, this paper constructs a measurement index system for the symbiotic level of digital innovation ecosystems from three dimensions: the symbiosis of digital innovation subjects, the digital innovation environment, and digital innovation interaction. This paper applies the entropy weight TOPSIS method, Dagum Gini coefficient decomposition, and spatial convergence analysis to empirically examine the symbiotic levels, regional disparities, and spatial convergence of China’s digital innovation ecosystem. The results are as follows: (i) At the national level, the symbiotic level of China’s digital innovation ecosystem has generally increased, creating a spatial distribution pattern that is “high in the east, flat in the middle, and low in the west”. (ii) From a regional perspective, the major disparities between regions are the primary factors contributing to the overall difference in the symbiotic level of China’s digital innovation ecosystem. (iii) From the perspective of σ convergence, regional disparities in the symbiotic level of the digital innovation ecosystem are constantly expanding, and uneven regional development is intensifying. (iv) From the perspective of absolute β convergence, regions with lower levels of symbiosis in the digital innovation ecosystem have a faster growth rate of symbiosis than regions with higher levels of symbiosis, and there is a certain spatial spillover effect. (v) From the perspective of conditional β convergence, economic structure and innovation application can accelerate the spatial convergence of China’s digital innovation ecosystem symbiosis to a certain extent.

The green technology innovation system is a fundamental method for China to achieve its goals of carbon peak and carbon neutrality. Clarifying the relationship between two-way foreign direct investment (FDI) synergy and regional green technology innovation is key to the green transformation and sustainable development of regional innovation systems. Based on panel data from 30 provinces in China from 2009 to 2020, a threshold-panel-regression technique is used. Command-controlled environmental regulation (CER), market-incentive environmental regulation (MER), and public-participation environmental regulation (PER) are taken as threshold variables, and the threshold effect of two-way FDI synergy on regional green technology innovation under heterogeneous environmental regulation is empirically explored. The results show the following. (i) The effects of two-way FDI synergy on regional green technology innovation exhibit significant threshold characteristics with heterogeneous environmental regulation as a double threshold. (ii) As the threshold values of CER and PER increase, the promoting effect of two-way FDI synergy on regional green technology innovation first increases and then decreases. (iii) As the MER threshold value increases, the promoting effect of two-way FDI synergy on regional green technology innovation continues to increase. (iv) Under the medium-threshold condition of PER, the promoting effect of two-way FDI synergy reaches its greatest value. (v) The intensity of intellectual property protection, the number of regional innovation institutions, and the level of transportation infrastructure all have significant positive effects on regional green technology innovation, and the number of regional innovation institutions exhibits the greatest promoting effect. This study provides new insights into two-way FDI synergy and methods to promote green technology innovation, and these findings can help the government formulate future policies and strategies to promote regional green technology innovation.

Zirconia ceramics are promising materials for restoration and are widely used in the field of artificial teeth. However, wear resistance affects the longevity of artificial teeth. In this study, peacock tail feather micro-textures and groove micro-textures are prepared on the surfaces of zirconia ceramics via the laser ablation technique to improve their tribological properties. The effects of micro-textures on the surface wettability and tribological properties of zirconia ceramics are studied. The micro-textures improve the surface wettability and tribological properties of zirconia ceramics. The average coefficient of friction of peacock tail feather micro-textured samples decreases by 53% compared to that of the samples without micro-textures. Different operating conditions affect the friction properties of zirconia ceramics. The samples have the best friction performance when the rotational speed, load, and acid/alkaline environment are 200 r/min, 15 N, and weakly alkaline, respectively. Furthermore, the mechanism by which surface micro-textures reduce frictional wear is as follows: the textured grooves store debris, and the bottom edge of the textured groove acts as a cutting tool to cut debris, preventing debris from scratching the surface. The micro-textures store lubricant and form a liquid film on the ceramic surface to reduce wear.