Value-added services exert a substantial impact on the interaction between startups and investors, leading to a win–win situation. Exploring the mechanisms through which investors exert their influence on the value-added services offered to startups can facilitate this goal. Such an investigation can aid startups in increasing their value, while also enabling investors to reap benefits through investment appreciation. Additionally, it can facilitate the growth of the equity investment industry in a healthy manner. As part of this study, six startups that have received value-added services from investors have been selected as typical cases. A SETC theoretical model has been constructed using grounded theory to extract the main influencing mechanisms of the value-added services’ effects. The research results show that value-added services, in addition to directly affecting the value-added service effect, may also instigate principal-agent conflicts between investors and startups, driven by the external environment and the both parties’ traits, which ultimately influence the value-added service effect. Value-added service is an internal direct driver of the value-added service effect; the external environment is a external direct driver, both parties’ traits are situational drivers, and principal-agent conflict is an intermediary driver.
To investigate the diffusion degree of low-carbon technology in competitive firms and the influence of different pollution regulations, we constructed an evolutionary game model representing three environmental mechanisms: total amount control and trading, carbon tax, and subsidy, within a complex firm network. By analyzing the effects of carbon quotas, tax rates, and subsidy rates, we comprehensively assessed the performance of these mechanisms in terms of diffusion degree, firm profits, consumer surplus, environmental damage, and social welfare. The study results demonstrated distinct outcomes for each environmental mechanism. Under the subsidy mechanism, low-carbon technology exhibited the highest diffusion degree, suggesting its efficacy in promoting widespread adoption. However, it is worth noting that the higher the subsidy, the more environmental pollution it led to, which presents a trade-off between environmental benefits and financial incentives. On the other hand, the carbon tax mechanism resulted in minimal pollution, reflecting its potential as an effective tool for environmental regulation. Finally, the cap-and-trade mechanism emerged as the most favorable option, as it maximized social welfare while effectively addressing environmental concerns.
Our main purpose is to investigate the dynamic control problem of a monopolist’s product and process innovation under reference quality. The main features of this article are: (i) a monopolist dealing with customer behaviour in the spirit of the principle of behaviour economics determines the product price, and carries out the activities of product and process innovation; (ii) the consumers’ demand depends on price, product quality and reference quality, and adopts an additive separable demand function form. Our main results show that under the cases of the monopolist optimum and the social planner optimum, (i) there exists an unique stable, which is a saddle-point steady-state equilibrium; (ii) the change rates of the monopolist’s investments in product and process innovation are increasing with the reference quality, while the monopolist’s steady-state investments in product and process innovation are decreasing with the reference quality; (iii) as the memory parameter increases with other parameters kept constant, it is very likely that the monopolist’s investment in process innovation be greater than the investment in product innovation; and (iv) the social incentive towards both investments in product and process innovation is always larger than the private incentive characterizing the profit-seeking monopolist.
We provide the first systematic analysis of the stock return lead-lag effect among firms connected through shared analyst coverage in China’s A-share markets. We measure the shared analysts-weighted average returns of connected firms （CF） and show that CF return is a significant positive predictor of future returns of the focal firms in the following one to 12 months. The CF-based long-short portfolio earns an abnormal return of 10% to 12% per year. The effect is robust to controls for the industry and geographic momentum effects. Further evidence shows that the CF momentum spillover effect is stronger when the focal firm shares more analysts with connected firms， is covered by more non-star analysts or analysts with lower levels of education， or is held by more stress-resistant institutional investors. Our findings contribute to the cross-asset momentum literature by documenting a new， strong， and long-lasting momentum spillover effect in the Chinese stock markets.
Additive network DEA model is one kind of highly nonlinear programming problem,which is difficult to be solved directly.The existing heuristic algorithm cannot be applied to obtain the exact solution of the model,and will consumes a lot of computing resources and times in the big data environment.In order to solve these two issues,the presented study mainly does two aspects of work.Firstly,aiming at the issue of solving precision of the model,a solving method of quadratic fractional programming is proposed in this study,which decomposes the model into a finite quadratic programming,and it is proved theoretically that the presented method can be applied to obtain the exact solution of the model.Then,in view of the issue of the slow solving speed in the big data environment,this work optimized the model's constraints by reducing the number of constraints and the consumption of computing resources while the feasible region remained unchanged,so as to improve the solving speed of the model.The numerical case results show that the proposed method can effectively improve both of the calculation accuracy and speed of the additive two-stages DEA model.
