This study examines the asymmetric link between fiscal decentralization, environmental innovation, and carbon emissions in highly decentralized countries. Our preliminary findings strictly reject the preposition of data normality and highlight that the observed relationship is quantile-dependent, which may disclose misleading results in previous studies using linear methodologies. Therefore, a novel empirical estimation technique popularized as Method of Moments Quantile Regression is employed that simultaneously deal with non-normality and structural changes. The results exhibit that fiscal decentralization significantly mitigates carbon emissions only at lower to medium emissions quantiles. On the other hand, environmental innovation reduces carbon emissions only at medium to higher emissions quantiles. Interestingly, the emissions-reducing effect of fiscal decentralization is highest for lower emissions quantiles and lowest for higher emissions quantiles. In contrast, the impact of environmental innovation is lowest for lower emissions quantiles and highest for higher emission quantiles. Economic growth and population increase carbon emissions, and their emissions-increasing effect are lowest for lower emissions quantiles and highest for higher emissions quantiles. Moreover, the heterogeneous panel causality test confirms a one-way causal association, implying that any policy intervention regarding fiscal decentralization and environmental innovation significantly affects carbon emissions.

Technological adaption and innovative activities foster small and medium enterprises (SMEs) growth by allowing production and process diversifications. Furthermore, open innovation practices, especially SMEs, rely on several firms’ specific attributes, and their impact varies accordingly. This study’s motivation is to explore the impact of technological adaptation and open innovation on SMEs run by women entrepreneurs and the challenges encountered in implementing open innovation. A sample of 580 questionnaires was sent to target SMEs, following the stratified random sampling technique, of which a complete 375 responses were duly received. The open innovation has been measured through eight innovative practices, reflecting the exploration and exploitation of technology in SMEs. This study found that women-owned enterprises were involved in many open innovation policies during the last five years. The result of this study indicated that there are no significant differences between manufacturing and industry regarding open innovation practices. Still, women-owned enterprises are more impressively engaged in open innovation practices. The research also identified that women-owned SMEs follow open innovation, mainly for market-related intentions, to compete with competitors and meet customers’ demands. The study contributes to the theoretical and practical implications. Further, the study is helpful for SMEs, researchers, practitioners, and decision-makers.

The scientific and technological innovation ability of the economic free trade zone is crucial to the depth and breadth of its economic development. There are too many subjective factors in the evaluation of the scientific and technological innovation ability of traditional economic free trade zones. In order to objectively evaluate the scientific and technological innovation ability of the free trade zone, this paper uses the random forest weighting method and the weighted linear combination to construct the evaluation index system, designs the evaluation model of the scientific and technological innovation ability of the free trade zone, and makes a specific analysis and evaluation based on the operation data of the economic and technological innovation ability of China’s four key free trade zones in 2020. The results show that the scientific and technological innovation ability of Guangdong economic free trade zone is the strongest, followed by Guangdong economic and trade zone, Shanghai economic and trade zone, Zhejiang economic and trade zone, and Tianjin economic and trade zone; Guangdong free trade zone has strong scientific and technological innovation ability. Compared with other free trade zones, Guangdong’s main advantages lie in the integration and aggregation ability of the industrial chain, strong policy support, and talent attraction. The scientific and technological innovation ability forms a virtuous circle. The analysis of the model example shows that the introduction of the random forest weighting method into the scientific and technological evaluation of the free trade zone can more objectively compare and analyze the scientific and technological innovation ability of the free trade zone, which is of great significance to help the free trade zone find out the problems and shortcomings in the scientific and technological innovation ability and improve the level of scientific and technological innovation.

The steps of generating basic data by the LDA model and calculating text by the weighted algorithm have a good effect on text clustering. In this paper, the LDA topic model is used to effectively improve the accuracy of strategy text clustering. FTZ economics text clustering simulates FTA economics text data and economic data, imports economics and economic figures and word lists, and uses the traditional vector space model for factor representation. After that, the text vectors are independent of each other, ignoring the semantic relationship, which affects the clustering analysis results. A Chinese text clustering algorithm based on semantic clustering is proposed. Based on the principle of cooccurrence and semantic relevance of words, the algorithm uses the collocation vector of feature words to construct semantic clustering; find the document vector with embedded semantic information. Finally, document vectors with embedded semantic information are used. Finally, K vector is used for cluster analysis. The simulation analysis in this paper shows that the economic growth of the free trade zone is the largest under the economics guidance, which can reach 15%.

With the establishment and rapid development of the China (Shanghai) Pilot Free Trade Zone (FTZ), the scale of enterprises in the zone has grown rapidly. This paper takes the actual needs of the Shanghai FTZ as the background, extracts key information such as entities from the Big Data related to Internet enterprises, further constructs the enterprise knowledge graph, and applies it to the supervision and service of the FTZ. The enterprise knowledge graph is constructed using the Neo4j graph database. To verify the effectiveness of the named entity identification and relationship extraction methods proposed in this paper, experiments were conducted to validate them, and both achieved good results.