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In this study, numerical simulations are performed to compare the adiabatic film cooling effectiveness and reveal the difference of film cooling mechanisms of two models with the same geometries and cross-section areas of film holes’ exits at three typical blowing ratios (M = 0.5, 1 and 1.5). The two models are an elliptical model and a cylindrical model with 90° compound angle, respectively.

Three different cases are considered in this work and the baseline is the model with a cylindrical film hole. The same boundary conditions and a validated turbulence model (realizable k-ε) are adopted for all cases.

The results show that both the elliptical and cylindrical models with 90° compound angle can enhance the film cooling effectiveness compared with the baseline. However, the elliptical model performs well at lower blowing ratios and in the near region at each blowing ratio because of the wider width of the film hole’s exit. The cylindrical model with 90° compound angle provides better film cooling effectiveness in the further downstream area of the film hole at higher blowing ratio because of the less lift-off and better coolant coverage in the larger x/D region along the mainstream direction.

Overall, it can be concluded that although the elliptical and cylindrical models with 90° compound angle have identical hole exits, the different inlet direction and cross-sectional geometry affect the flow structures when the coolant enters, moves through and exits the hole and finally different film cooling results appear.

This paper aims to study the anodization of aluminum in a mixture solution of 1,3-propanediol solutions and 0.4 mol l⁻¹ H₃PO₄ at a low temperature.

The morphology and composition of the resulting anodic aluminum oxide (AAO) template was characterized by means of a scanning electron microscope in combination with an energy dispersive spectrometer.

Pore density and pore diameter both were found to be dependent on the temperature of anodization.

The resulting AAO templates exhibited uniform and regular pores with diameters that were significantly smaller than those found in AAO templates anodized at room temperature.

This study aims to clarify the mechanism of film hole location at the span-wise direction of an internal cooling channel with crescent ribs on the adiabatic film cooling performance, three configurations are designed to observe the effects of the distance between the center of the ellipse and the side wall(Case 1, l = w/2, Case 2, l = w/3 and for Case 3, l = w/4).

Numerical simulations are conducted under two blowing ratios (i.e. 0.5 and 1) and a fixed cross-flow Reynolds number (Re_c = 100,000) with a verified turbulence model.

It is shown that at low blowing ratio, reducing the distance increases the film cooling effectiveness but keeps the trend of the effectiveness unchanged, while at high blowing ratio, the characteristic is a little bit different in the range of 0 = x/D = 10.

These features could be explained by the fact that shrinking the distance between the hole and side wall induces a much smaller reserved region and vortex downstream the ribs and a lower resistance for cooling air entering the film hole. Furthermore, the spiral flow inside the hole is impaired.

As a result, the kidney-shaped vortices originating from the jet flow are weakened, and the target surface can be well covered, resulting in an enhancement of the adiabatic film cooling performance.

Granular materials possess multiscale structures, i.e. micro-scales involving atoms and molecules in a solid particle, meso-scales involving individual particles and their correlated structure, and macroscopic assembly. Strong and abundant dissipations are exhibited due to mesoscopic unsteady motion of individual grains, and evolution of underlying structures (e.g. force chains, vortex, etc.), which defines the key differences between granular materials and ordinary objects. The purpose of this paper is to introduce the major studies have been conducted in recent two decades.

The main properties at individual scale are introduced, including the coordination number, pair-correlation function, force and mean stress distribution functions, and the dynamic correlation function. The relationship between meso- and macro-scales is analyzed, such as between contact force and stress, the elastic modulus, and bulk friction in granular flows. At macroscales, conventional engineering models (i.e. elasto-plastic and hypo-plastic ones) are introduced. In particular, the so-called granular hydrodynamics theory, derived from thermodynamics principles, is explained.

On the basis of recent study the authors conducted, the multiscales (both spatial and temporal) in granular materials are first explained, and a multiscale framework is presented for the mechanics of granular materials.

It would provide a paramount view on the multiscale studies of granular materials.

The authors investigate the extent to which online talk can influence contemporaneous and future stock trading, especially when market news is unpresented.

The authors propose an improved sentiment formula incorporating online hype, neutral sentiment and poster reputation. In addition, they conduct event study, OLS regression analyses and probit models.

First, investors tend to be more talkative in relation to firms that are (1) smaller size, (2) more growth-like, (3) with lower prices and higher short interests and (4) of higher beta. Second, the bullish tone of investors positively affects the abnormal returns of small-capitalization stocks. However, online talk has little impact on large-capitalization stocks, except that more postings boost trading liquidity. Third, online talk predicts the presence of future news regardless of firm size, with stronger predictive power found for small-capitalization stocks.

It is of interest to practitioners and researchers to study online talk so as to better understand the trading psychology of retail investors and the effects on the stock market. Furthermore, policymakers are interested in tracking activities on stock message boards in order to prevent security fraud and protect investors' interests.

The results are robust and suggest that online talk has significant impacts on stock trading exploiting an information asymmetry. This study of stock message board posting activities helps researchers to understand whether message contents contain valuable and unique content compared with information available via more traditional media channels.

This study aims to combine two fraud-related streams of the literature on guanxi and overconfidence into an integrated framework, which is the fraud triangle, to interpret the mechanism of fraud commission and detection.

A bivariate probit model with Partial Observability (POBi Probit) is applied. Moreover, the POBi Probit model is adjusted to the Chinese context. The China-specific POBi Probit model is constructed using data of Chinese A-share listed companies from 2008 to 2014, with a total of 15,109 firm-year observations.

Overconfidence induces fraud commission and worsens fraud detection; overconfidence mediates the relationship between fraud and guanxi; the “white side” of guanxi comes from alumni networks, while the “dark side” is derived from relatives-based networks; overconfidence induces fraud commission in accounting and disclosure and benefits the detection of disclosure frauds. Guanxi suppresses fraud commission in management and disclosure, however, it worsens fraud detection given fraud in management and disclosure; overconfidence induces fraud commission in both state-owned enterprises (SOE) and non-SOEs, and benefits fraud detection in SOEs. Guanxi suppresses fraud commission and worsens fraud detection in SOEs and city-owned firms.

There are two drawbacks of the partial observable bivariate probit (POBi-Probit) method that must be mentioned here. On one hand, the ex ante variable selection is one of the most difficult parts of applying the POBi-Probit model and different variables are included in different studies. On the other hand, the POBi-Probit model might not converge if too many variables are included. Thus, many widely accepted factors can be included in the model. Thus, this study initially sets the POBi-Probit model based mainly on Khanna et al. (2015) and then adjusts the model for the Chinese context (e. g. considering government ownership) according to Yiu et al. (2018) and Zhang (2018) and the local study of Meng et al. (2019). Considering the observability of fraud, on one hand, the observability of fraud commission is a widely accepted limitation, especially when accounting opacity comes across with regulatory efficiency (Yiu et al. (2018). On the other hand, the observability of relationships is another obstacle to this study. Future studies can go further by revealing the presently unobservable relationships using Big Data technology.

This paper theoretically and practically contributes to the literature on both corporate fraud and corporate governance. Theoretically, by introducing integrated principal-agent resource-reliance theory (IPRT) and upper echelon theory (UET), this paper broadens the framework of fraud triangle theory (FTT) and testifies the availability of the broaden FTT in the transitional and emerging-market context of China. Practically, this paper provides evidence that guanxi and overconfidence are two of the factors affecting corporate fraud. Thus, this paper provides a governance approach opposing corporate fraud in China, which may help the other emerging economies in transition.

Firms increasingly diversify their technological competencies to achieve different strategic objectives. This study aims to explore the impacts of technological knowledge characteristics on patenting choices for inventions created by subsidiaries in an uncertain and fast changing environment.

The data used in this study are patents granted to the world largest firms by the USPTO for inventions attributable to their subsidiaries in China between 1996 and 2005. In addition, the patent data from State Intellectual Property Office (SIPO) of China are used for the matching in terms of filing patent applications in both USA and China for a same piece of technology. A discrete Logit model is used to examine the effects of technological distance and categories on Chinese patent application and international priority.

The findings suggest that firms have priority to seek international patent protection, instead of host country protection, for valuable subsidiary inventions in their background and marginal technological fields. In addition, a firm may seek host country legal protection simultaneously for inventions built upon knowledge from technologically distant fields.

As we are more interested in protecting technological knowledge, the protection of other types of knowledge, such as organizational knowledge, deserves further research attentions. Moreover, future research may expand current study by including small and medium firms, as well as firms in other developing economies.

While the economic and legal environment in China may have evolved since studied period, the results have practical implications for firms in other developing countries that are at an early stage of catching-up or those in a host location featuring a similar uncertain and fast changing environment. In particular, the study suggests that foreign firm managers would have more strategic choices of patenting than local firms in the host country. For strategically important inventions bridging complex knowledge from different technological areas, firms could seek protection in multiple countries simultaneously, including both home country and other major markets. Furthermore, managers could choose whether or not to protect a particular category of technologies in host country depending on value of the technology to the firm and the IPR protection of host country. Finally, the approach of looking at knowledge-level characteristics, which can be easily measured through readily available intra-firm information, provides managers with a practical and useful tool to make these strategic decisions.

This study represents an effort to extend the understanding on how foreign MNCs could generate and appropriate valuable technologies in an uncertain and fast-changing environment. In particular, the authors focus on how MNCs could use different international patenting patterns to benefit from subsidiary inventions. Whereas previous literature mainly focuses on country-level and firm-level determinants, this study approaches the topic through the lens of knowledge-level factors. By studying how knowledge characteristics determine firm strategic behaviors, the authors offer additional justifications of the knowledge-based view of the firm. Meanwhile, the findings enrich our understanding of an important component of MNC’s global strategies in managing their technologies through selectively patenting in different locations. Firms pursue diversified technologies for different strategic objectives. As subsidiary inventions become a very important source of firm competitiveness, MNCs have to face the trade-off between higher patenting costs and the appropriability of subsidiary generated knowledge. The findings suggest that it is not necessary for MNCs to protect all subsidiary inventions in host countries.

The suppliers of experimental resources required in megaprojects are driven by short-term interests, presuming that participation in the digital platform would only increase their inputs and fail to rapidly expand their revenue, resulting in their insufficient motivation to participate. This paper aims to design effective incentives for these suppliers exhibiting the aforementioned behaviour to drive them to participate and actively share their resources on the platform.

This paper develops incentives for applying the digital platform for experimental resource sharing by using a reverse induction approach to model and solve an incomplete information game. It compares the traditional experiment management mode and the new mode of applying the digital platform, taking the degree of sharing experimental resources on the platform as the variable and constructing three incentive models. By analysing these different degrees of sharing and the different experimental and informatisation capabilities of the suppliers, it could obtain the optimal incentive scheme for changes in sharing behaviour.

The results show that the designed incentives could increase the participation of suppliers in the platform and the number of their shared resources and make the benefits of both the supplier and the demand side reach the optimal state of a win-win situation. However, a higher degree of sharing by suppliers does not yield better results. In addition, the incentive coefficients for this degree should be set based on the suppliers’ different experimental and informatisation capabilities and the ratio of input cost-sharing, so as to avoid blind inputs from both supply and demand.

This study fills the research gap regarding incentives of the digital platform of experimental resource-sharing for megaprojects; it contributes to the body of knowledge by providing a quantitative perspective of understanding the experimental resource-sharing behaviour that motivates the usage of the digital platform. Furthermore, it reveals the incentive mechanism for application in different scenarios, and quantitative analysis is conducted to provide practical insights into promoting the new experiment management mode in megaprojects for more effective incentivisation.

In recent years, the frequency of emergencies, such as natural disasters and public health crises, has markedly increased globally. These occurrences have introduced new challenges to national public security systems and emergency management capabilities. Post-disaster humanitarian logistic operations involve the collection of emergency relief resources to mitigate the impact of disasters in affected areas. Effective coordination among governments, enterprises and charities is essential to enhance the efficiency of these operations. This study employs evolutionary game theory to explore the strategic interactions and behavioral patterns among these key stakeholders during the collection of emergency materials.

A tripartite evolutionary game model involving governments, enterprises and charities is developed. Subsequently, to validate the theoretical findings, a scale-free network is constructed for the purpose of numerical simulations. As this network evolves, both the edges between nodes and the strategy choices of the nodes also change. Numerical simulations are conducted using the network to examine the sensitivity of factors influencing strategic choices among game stakeholders.

According to the model simulation results, penalties significantly influence government regulation strength, while enterprise philanthropic behavior is mainly affected by penalties, profit transfer benefits and trust loss. For charities, strategic choices are primarily driven by penalties, tax subsidies, illegal operation benefits and charitable costs. The findings provide a theoretical basis for governments, enterprises and charities to select the sensible strategy.

Our study establishes a dynamic network of edges and nodes evolving over time to analyze the strategic evolutionary paths of governments, enterprises and charities from a micro perspective. The results assist governments, enterprises and charities in making more strategic decisions.

The purpose of this study is to explore the relationship between big data and supply chain platform in China’s retail industry. With the emergence of big data resources and technologies, the business pattern of new retail advocates the combination of online and offline channels. Supply chain platform plays a key role in the implementation of retail activities, which has gradually become a research hotspot in the cross field of operations management and information system.

Through the method of literature review and case study, this study empirically explores how big data shapes supply chain platform to support new forms of online retail by grounded theory.

The model framework is validated by reliability test and coding method to process survey materials. The results identify the overall antecedents of supply chain platform and reveal positive effects between big data and new retail. The findings help firm managers build a big data-driven supply chain to support new retail.

There are insufficient studies on theoretical frameworks and interaction relationships among big data, supply chain platform and new retail.