Technological innovations in the power industry can help reduce electricity consumption but may also have a negative result due to rebound effects. Estimation and refinement of electricity demand rebound effects are important for assessing the impact of technological innovations. For this purpose, this paper first constructs a Log Mean Divisia Index (LMDI) to measure the structural and technical effects. Secondly, a Data Envelopment Analysis (DEA)–Malmquist Productivity Index is used to calculate the change in the generalized rate of technological progress, narrow rate of technological progress, and technical use efficiency. Thirdly, the electric power demand rebound effect during the New Normal period is calculated to compare with the rebound effect of the overall energy. Finally, a vector auto-regressive (VAR) model and an impulse response function (IRF) are used to investigate the impact degree of electric power demand changes on other energy demand under the “electrical energy substitution” strategy. The empirical results indicate that the general technological progress rate of China’s electric power industry is increasing gradually in the New Normal period, and the variations in electric demand exhibit the characteristics of the backfire effect and partial rebound effect, respectively, in the context of generalized technological innovation and narrow technological innovation. Meanwhile, contrary to the changing trend of the overall energy demand intensity, electric power demand intensity increased continuously with the advancement of the “electrical energy substitution” strategy, which led to a continuous decline in other energy demands.

Taking 518 technology mergers and acquisitions of new generation information technology listed companies in Shanghai and Shenzhen A shares from 2013 to 2017 as research samples, this paper further studies the regulating effect of absorptive capacity and the mediating effect of marketing ability on the basis of empirical testing of target knowledge base and the market competitiveness of the acquirer by constructing a regulating model with intermediary. It is found that: (1) Target knowledge base has a positive impact on the market competitiveness and marketing ability of the acquirer; (2) marketing ability plays an intermediary effect between target knowledge base and the market competitiveness of the acquirer; (3) absorptive capacity has a positive regulating effect on target knowledge base and the marketing ability of the acquirer. The regulating effect of absorptive capacity on target knowledge base and the market competitiveness of the acquirer is partially realized through the intermediary of marketing ability.

This study analyzes the process of corporate reputation (CR) propagation. We consider that different positions play different roles via social word of mouth (sWOM). In essence, our interest lies in the following question: how does sWOM affect the process of CR propagation? As a benchmark, we develop a dynamic model to reflect the factors and laws influencing corporate reputation propagation. We find that the stability of the system is not what corporations want to see in the propagation of positive CR after analyzing two basic reproduction numbers and conducting a numerical simulation. Another important finding is that stability is what corporations expect in the propagation of negative CR. This study makes the logical analysis of the relationship between CR and consumer loyalty more complete and helps us to clearly understand the overall process of CR propagation. The study provides a new way to analyze the law of CR propagation and can provide a reference for decision-making for corporations.