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This paper outlines the rapid rise of China's fintech companies over the past decade with a focus on their globalization strategies as they enter their next phase of development.

The author examines China's current and prospective influence on global financial digitization trends, and assesses both domestic and foreign opportunities and challenges confronted by China's fintech firms as they look to expand abroad.

The Chinese government is experimenting with a radically new fintech system and a regulatory regime in response to it. Chinese ambitions to expand fintech influence through private companies and the state-led “digital RMB” (e-CNY) will likely provoke a wave of “digital protectionism” among developed nations to protect internal digital payments.

This paper is an original economic history research on China's fintech industry.

This study aims to examine the impact of the gameful experience on behavioural outcomes. Drawing from stimulus–organism–response theory, it proposes and tests a new model that investigates the relationship between the gameful experience, brand loyalty and intention to use gamified branded applications in the sports context. In addition, it explores the mediating role of customer–brand engagement (CBE) and the moderating role of self-image congruity (SIC).

A sample of 436 active users of sport-related branded gamified applications was used to test the model. Data was collected from online sports forums, brands’ Facebook communities and during sporting events.

Results indicate that the gameful experience positively and directly impacts behavioural intentions but does not directly influence brand loyalty. This relationship becomes partially significant when mediated by CBE. In addition, results show that users with high levels of SIC are more likely to continue using the gamified application, whereas users with low levels are more likely to engage with the brand.

This study expands the gamification literature in the sports sector by revealing the importance of the gameful experience in driving loyalty, behavioural intentions and CBE. It proposes a new model that sheds light on the emotional aspect of the interaction between a user and a gamified system and the importance of exploring the effects of moderators, such as SIC, in these relationships.

The purpose of this paper is to show how the EStra-Many method works on optimization problems characterized by high-dimensionality of the objective space. Moreover, a comparison with a more classical approach (a constrained bi-objective problem solved by means of NSGA-II) is done.

The six reactances of a compensation network (CN) for a wireless power transfer system (WPTS) are synthesized by means of an automated optimal design. In particular, an evolutionary algorithm EStra-Many coupled with a sorting strategy has been applied to an optimization problem with four objective functions (OFs). To assess the obtained results, a classical genetic algorithm NSGA-II has been run on a bi-objective problem, constrained by two functions, and the solutions have been analyzed and compared with the ones obtained by EStra-Many.

The proposed EStra-Many method identified a solution (CN synthesis) that enhances the WPTS, considering all the four OFs. In particular, to assess the synthesized CN, the Bode diagram of the frequency response and a circuital simulation were evaluated a posteriori; they showed good performance of the CN, with smooth response and without unwanted oscillations when fed by a square wave signal with offset. The EStra-Many method has been able to find a good solution among all the feasible solutions, showing potentiality also for other fields of research, in fact, a solution nondominated with respect to the starting point has been identified. From the methodological viewpoint, the main finding is a new formulation of the many-objective optimization problem based on the concept of degree of conflict, which gives rise to an implementation free from hierarchical weights.

The new approach EStra-Many used in this paper showed to properly find an optimal solution, trading-off multiple objectives. The compensation network so synthesized by the proposed method showed good properties in terms of frequency response and robustness. The proposed method, able to deal effectively with four OFs, could be applied to solve problems with a higher number of OFs in a variety of applications because of its generality.