Search

Innovation is the source of competitive advantage for enterprises. In the context of global industrial upgrading and increasingly fierce technological competition, enhancing innovation capabilities is key to enterprises' success. Technology mergers and acquisitions have become an important way for enterprises to acquire external technology, to enhance their innovation capabilities, and to achieve rapid development. Many scholars have extensively researched technology mergers and acquisitions and enterprise innovation. This paper summarizes the relevant research literature according to different research contents. The research content includes the motivation for technology mergers and acquisitions, analyzing the impact mechanism and the path of technology mergers and acquisitions regarding enterprise innovation from the perspectives of technology relevance, the technology absorption capacity, the institutional environment, and corporate governance, as well as related research on the consequences of technology mergers and acquisitions for enterprise innovation and measuring methods for technology mergers and acquisitions and enterprise innovation. This paper summarizes and organizes the relevant literature, aiming to find research directions and enrich future research fields by summarizing it. This effort provides important theoretical support for the strategic decision-making of enterprise technology mergers and acquisitions under the guidance of innovation, and it also provides a reference for further optimizing the innovation incentive environment. [ABSTRACT FROM AUTHOR]

The main drivers of the continental Northern Hemisphere snow cover are investigated in the 1979–2014 period. Four observational datasets are used as are two large multi-model ensembles of atmosphere-only simulations with prescribed sea surface temperature (SST) and sea ice concentration (SIC). A first ensemble uses observed interannually varying SST and SIC conditions for 1979–2014, while a second ensemble is identical except for SIC with a repeated climatological cycle used. SST and external forcing typically explain 10 % to 25 % of the snow cover variance in model simulations, with a dominant forcing from the tropical and North Pacific SST during this period. In terms of the climate influence of the snow cover anomalies, both observations and models show no robust links between the November and April snow cover variability and the atmospheric circulation 1 month later. On the other hand, the first mode of Eurasian snow cover variability in January, with more extended snow over western Eurasia, is found to precede an atmospheric circulation pattern by 1 month, similar to a negative Arctic oscillation (AO). A decomposition of the variability in the model simulations shows that this relationship is mainly due to internal climate variability. Detailed outputs from one of the models indicate that the western Eurasia snow cover anomalies are preceded by a negative AO phase accompanied by a Ural blocking pattern and a stratospheric polar vortex weakening. The link between the AO and the snow cover variability is strongly related to the concomitant role of the stratospheric polar vortex, with the Eurasian snow cover acting as a positive feedback for the AO variability in winter. No robust influence of the SIC variability is found, as the sea ice loss in these simulations only drives an insignificant fraction of the snow cover anomalies, with few agreements among models. [ABSTRACT FROM AUTHOR]

The role of surface ocean anomalies for the continental Northern Hemisphere snow cover is investigated, together with the interactions between snow cover and atmosphere. Four observational datasets and two large multi-model ensembles of atmosphere-only simulations are used, with prescribed sea surface temperature (SST) and sea ice concentration (SIC). A first ensemble uses observed interannually varying SST and SIC conditions for 1979–2014, while a second ensemble is identical except for SIC where a repeated climatological cycle is used. SST and external forcing typically explain 10 to 25 % of the snow cover variance in model simulations, with a dominant forcing from the tropical and North Pacific SST, while no robust influence of the SIC is found. In observations, the Ural blocking is the main driver of the November and April snow cover over Eastern Eurasia, while the North Atlantic Oscillation (NAO) dominates the snow cover forcing in January. In November and more robustly in January, dipolar anomalies of snow cover over Eurasia, with positive anomalies over Europe and negative anomalies over Southern Siberia, also precede the Arctic Oscillation (AO) by one month. In models, snow cover over western Eurasia in January also precedes by one or two months a negative AO phase. The detailed outputs from one of the models suggest that both the western Eurasia snow cover and polar vortex are generated by Ural blocking, and that both snow cover and polar vortex anomalies act to generate the AO one or two months later. [ABSTRACT FROM AUTHOR]

It is now well established that the Arctic is warming at a faster rate than the global average. This warming, which has been accompanied by a dramatic decline in sea ice, has been linked to cooling over the Eurasian subcontinent over recent decades, most dramatically during the period 1998–2012. This is a counterintuitive impact under global warming given that land regions should warm more than ocean (and the global average). Some studies have proposed a causal teleconnection from Arctic sea ice retreat to Eurasian wintertime cooling; other studies argue that Eurasian cooling is mainly driven by internal variability and the relationship to sea ice is coincidental. Overall, there is an impression of strong disagreement between those holding the "ice-driven" versus "internal variability" viewpoints. Here, we offer an alternative framing showing that the sea ice and internal variability views can be compatible. Key to this is viewing Eurasian cooling through the lens of dynamics (linked primarily to internal variability with a small contribution from sea ice; cools Eurasia) and thermodynamics (linked to sea ice retreat; warms Eurasia). This approach, combined with recognition that there is uncertainty in the hypothesized mechanisms themselves, allow both viewpoints (and others) to co-exist and contribute to our understanding of Eurasian cooling. A simple autoregressive model shows that Eurasian cooling of this magnitude is consistent with internal variability, with some periods being more susceptible to strong cooling than others. Rather than posit a "yes-or-no" causal relationship between sea ice and Eurasian cooling, a more constructive way forward is to consider whether the cooling trend was more likely given the observed sea ice loss, as well as other sources of low-frequency variability. Taken in this way both sea ice and internal variability are factors that affect the likelihood of strong regional cooling in the presence of ongoing global warming. [ABSTRACT FROM AUTHOR]

We have used an Atmospheric General Circulation Model with a large ensemble (300) to explore the atmospheric responses during the autumn-winter (September to February) to the projected sea-ice free Arctic in autumn (September to November). The detectability of the responses against the internal variability has also been studied. Three ensemble experiments have been performed, the control (CONT) forced by the simulated present-day Arctic sea-ice concentration (SIC) and sea surface temperature (SST), the second forced by the projected autumn Arctic SIC free and present-day SSTs (SENSICE) and the third forced by the projected autumn Arctic SIC free and projected SSTs (SENS). The results show that the disappearance of autumn Arctic sea-ice can cause significant synchronous near-surface warming and increased precipitation over the regions where the sea-ice is removed. The changes in autumn surface heat flux (sensible plus latent), surface air temperature (SAT) and precipitation averaged over the sea-ice reduction region between the SENS and the CONT are about 46, 43 and 50 % more respectively than the changes between the SENSICE and the CONT, which is consistent with the prescribed boundary setting: the surface temperature warming averaged over the sea-ice reduction region in the SENS relative to the CONT is 48 % higher than that in the SENSICE relative to the CONT. The response shows a significant negative Arctic Oscillation (AO) in the troposphere during autumn and December. However, the negative AO does not persist into January-February (JF). Instead, 500 hPa geopotential height (GH) response presents a wave train like pattern in JF which is related to the downstream propagation of the planetary wave perturbations during November-December. The SAT increases over northern Eurasia in JF in accordance with the atmosphere circulation changes. The comparison of the atmosphere response with the atmosphere internal variability (AIV) shows that the responses of SAT and precipitation in the Arctic far exceed the AIV in autumn and the response of the 500 hPa GH is comparable to the AIV in autumn, but none of the responses during JF exceeds the AIV. [ABSTRACT FROM AUTHOR]

Suo, L. and Yang, K., 2019. Connected transactions, targeted additional shares issuance and operational management efficiency—evidence from listed firms in coastal region of China.In: Gong, D.; Zhu, H., and Liu, R.(eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 935–939. Coconut Creek (Florida), ISSN 0749-0208. Using the sample data of 1isted firms in coastal region of China in 2010-2017, correlation analysis, paired test and the multiple regression analysis method, this paper studies the impact of connected transactions on asset injection of targeted additional shares issuance, and changes of connected transactions on changes of business management efficiency. The results show that: (1)Companies with more connected transactions are inclined to carry out asset injection by targeted additional shares issuance of new shares. (2)Connected transactions significantly decrease after the private placement.(3)Reduce of connected transactions can improve management efficiency after the targeted additional shares issuance. [ABSTRACT FROM AUTHOR]