Search results

The sustainable development of the platform economy has been hindered by the absence and alienation of platform corporate social responsibility. Previous studies have mainly focused on the contents and governance models for platform corporate social responsibility. This study seeks to explore which strategy participants choose in the governance of platform corporate social responsibility and their influencing factors.

Using a platform ecosystem approach, a quadrilateral evolutionary game model was developed, and the stabilities of subjects’ behavioral strategies and their combinations in various scenarios were analyzed. Additionally, the effects of key parameters on the system’s evolutionary path were simulated.

The ideal steady state system is achieved when platform enterprises, complementors and consumers adopt positive strategies while the government adopts lax regulation. Moreover, the evolutionary strategies of the subjects are influenced by several factors, including the participation costs of governance, the rewards and punishments imposed by platform enterprises, as well as the reputational losses of platform enterprises and complementors due to media coverage.

This study offers insights into improving the governance effectiveness of platform corporate social responsibility for managers and practitioners.

This study contributes to existing literature by considering the rational orientation of platform ecosystem members and revealing the interaction mechanisms among members. Furthermore, this study combines collective action theory and reputation theory to clarify the influencing factors on members’ behaviors.

Supercritical CO₂ (SC–CO₂) fracturing is a potential technology that creates a complex fracturing fracture network to improve reservoir permeability. SC–CO₂-driven intersections of the fracturing fracture network are influenced by some key factors, including the disturbances generated form natural fractures, adjacent multi-wells and adjacent fractures, which increase the challenges in evaluation, control and optimization of the SC–CO₂ fracturing fracture networks. If the evaluation of the fracture network is not accurate and effective, the risk of oil and gas development will increase due to the microseismicity induced by multi-well SC–CO₂ fracturing, which makes it challenging to control the on-site engineering practices.

The numerical models considering the thermal-hydro-mechanical coupling effect in multi-well SC–CO₂ fracturing were established, and the typical cases considering naturally fracture and multi-wells were proposed to investigate the intersections and connections of fracturing fracture network, shear stress shadows and induced microseismic events. The quantitative results from the typical cases, such as fracture length, volume, fluid rate, pore pressure and the maximum and accumulated magnitudes of induced microseismic events, were derived.

In naturally fractured reservoirs, SC–CO₂ fracturing fractures will deflect and propagate along the natural fractures, eventually intersect and connect with fractures from other wells. The quantitative results indicate that SC–CO₂ fracturing in naturally fractured reservoirs produces larger fractures than the slick water as fracturing fluid, due to the ability of SC–CO₂ to connect macroscopic and microscopic fractures. Compared with slick water fracturing, SC–CO₂ fracturing can increase the length of fractures, but it will not increase microseismic events; therefore, SC–CO₂ fracturing can improve fracturing efficiency and increase productivity, but it may not simultaneously lead to additional microseismic events.

The results of this study on the multi-well SC–CO₂ fracturing may provide references for the fracturing design of deep oil and gas resource extraction, and provide some beneficial supports for the induced microseismic event disasters, promoting the next step of engineering application of multi-well SC–CO₂ fracturing.

This study aims to conceptualize the characteristics of artificial intelligence (AI) dogs while exploring their applications in tourism and hospitality settings.

The total of 30 in-depth interviews were conducted, and data were analyzed through thematic analysis.

This study proposed differences between AI dogs and real dogs and human-like robots, core characteristics of AI dogs’ functions, a matrix of appearance and expectation regarding intelligence for AI dogs and human-like robots, the relationship between ethical barriers and task complexity, adoptions of AI dogs in different user segments and practical applications in hospitality and tourism settings, such as restaurants, city tour guides, extended-stay resorts and event organizations.

This research advances the field of tourism and hospitality studies by introducing the new concept of AI dogs and their practical applications. This present study adds new insights into the opportunities and contexts of human–robot interaction in the field of tourism and hospitality.

To the best of the authors’ knowledge, this research is one of the first studies of AI dogs in tourism and hospitality.

This paper investigates the distinctive role of the US stock exchanges in the process of international consolidation. Besides the USA's leading role in financial markets, the focus on the country is motivated by its uniqueness within the stock exchange consolidation landscape, since, on the one hand, it has been involved in two different stock exchange mergers – with Nasdaq and NYSE – and, on the other hand, it has experienced a “reversal”, having joined and then left the Euronext-NYSE platform.

To investigate the effect of the NYSE-Euronext split on cross-border holdings and the role of the US as a member of the consolidated platform, we adopt a feasible Generalized Least Squares specification correcting for both heteroskedasticity and general correlation of observations across destination-countries, with standard errors adjusted for two-way clustering at the investing-country and year levels.

Differently from other mergers, we find a weak sensitivity of US inward and outward cross-border investments to stock exchange consolidation, and, consequently, to its reversal. The data suggest that the larger, the more liquid and the more visible the involved stock exchanges are, the less sensitive cross-border investment is to consolidation. Drawing on the cross-listing and cross-delisting literature, we formulate the conjecture that this evidence can be explained by decreasing returns of foreign investment to consolidation: the extraordinary large size, liquidity and visibility of the US stock exchanges diminishes the value of the role played by stock exchange consolidation in reducing cross-border barriers among member countries, so that it makes also the effects of its retreat non-significant.

This paper is the first, to best of our knowledge, to investigate the mirror phenomenon, that is, the “consolidation reversal” process of the NYSE stock exchange, the purpose being to understand its consequences for cross-border holdings. In the first part of this paper, we document no significant effect of the 2014 reversal on cross-border investments. The apparent absence of this effect could be due either to a level of cross-border investments remaining equally high (denoting persistence in investors' behavior) or to an equally non-significant effect of consolidation and reversal of the US stock exchanges on cross-border equity investments. The evidence supports the latter hypothesis and reveals an overall weak sensitivity of US cross-border investments (inward or outward) to stock exchange consolidation and, consequently, to its reversal. We formulate the conjecture, tested in the second part of the paper, that this evidence is due to the presence of diminishing returns of exchange consolidation's scale for foreign investors: the extraordinary large size, liquidity and visibility of the US stock exchanges makes the role of stock exchange consolidation less valuable in dampening cross-border barriers; consequently, also the reversal phenomenon presents no sizeable effects.