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The purpose of this paper is to investigate the influence of sprue distributions on the flow field and temperature field of the cladding casting process and verify the simulation results by experiments.

A steady-state mathematic model for the coupling of fluid flow, heat transfer and solidification to describe the process of cladding casting was present. The effect of sprue distributions on melt flow and temperature field was discussed. Based on the numerical simulation results, the cladding billet was prepared successfully. Moreover, the model has been verified against by temperature measurements during the cladding casting process.

There is a good agreement between the measured and calculated results. The homogeneity of melt flow determines the formability of cladding billets and circular temperature difference affects the bonding of the two alloys. The AA4045/AA3003 cladding billet with no defects in size of f140/f110 mm was fabricated successfully. The alloy elements diffused across the interface and formed diffusion layer with a thickness of 15 µm. The interface bonding strength is higher than the tensile strength of AA3003, indicating the metallurgical bonding between two alloys.

The casting parameters are limited to the aluminum alloy cladding billet in size of f140/f110 mm in this paper.

There are few reports of cladding billet, which are used to prepare condense pipes of automotive engines. The effect of distribution schemes on the cladding casting process is rarely studied.

This study contributes to the management accounting (MA) literature by exploring the effect of managers’ perception of justice in the budgeting process (as a subsystem of MA) on their satisfaction and motivation to achieve organizational objectives. Drawing on the Habermasian concept of deliberative democracy, which underscores the importance of gaining legitimacy to achieve desirable outcomes, our analysis focuses on seven constructs related to situational and intrinsic participation, procedural and distributive justice, and attitude on two outcome constructs: satisfaction and motivation. We surveyed managers with an accounting background who are directly involved in the budgeting process and analyzed our data using partial least squares-based path analysis–structural equation modeling (PLS-SEM). The results of this study indicate that both dimensions of justice – distributive and procedural – are positively associated with participation, and in turn, positively impact satisfaction and motivation. Contrary to expectations, managers’ influence on the final budget does not seem to be as important as we expected. Budgeting is an important managerial function that involves setting targets based on an organization’s strategy and allocating resources for its execution. Such a fundamental process requires managers’ participation at various levels to ensure that the process is fair and just. Our study’s findings imply that justice perceptions are an essential fabric of organizational processes that drive human behavior. Specifically, our findings reveal that perception of justice influences participation and satisfaction and motivation.

The coal-fired power plants have been confronted with new operation challenge since the unified carbon trading market was launched in China. To make the optimal decision for the carbon emissions and power production has already been an important subject for the plants. Most of the previous studies only considered the market prices of electricity and coal to optimize the generation plan. However, with the opening of the carbon trading market, carbon emission has become a restrictive factor for power generation. By introducing the carbon-reduction target in the production decision, this study aims to achieve both the environmental and economic benefits for the coal-fired power plants to positively deal with the operational pressure.

A dynamic optimization approach with both long- and short-term decisions was proposed in this study to control the carbon emissions and power production. First, the operation rules of carbon, electricity and coal markets are analyzed, and a two-step decision-making algorithm for annual and weekly production is presented. Second, a production profit model based on engineering constraints is established, and a greedy heuristics algorithm is applied in the Gurobi solver to obtain the amounts of weekly carbon emission, power generation and coal purchasing. Finally, an example analysis is carried out with five generators of a coal-fired power plant for illustration.

The results show that the joint information of the multiple markets of carbon, electricity and coal determines the real profitability of power production, which can assist the plants to optimize their production and increase the profits. The case analyses demonstrate that the carbon emission is reduced by 2.89% according to the authors’ method, while the annual profit is improved by 1.55%.

As an important power producer and high carbon emitter, coal-fired power plants should actively participate in the carbon market. Rather than trade blindly at the end of the agreement period, they should deeply associate the prices of carbon, electricity and coal together and realize optimal management of carbon emission and production decision efficiently.

This paper offers an effective method for the coal-fired power plant, which is struggling to survive, to manage its carbon emission and power production optimally.

Bitcoin (BTC) is significantly correlated with global financial assets such as crude oil, gold and the US dollar. BTC and global financial assets have become more closely related, particularly since the outbreak of the COVID-19 pandemic. The purpose of this paper is to formulate BTC investment decisions with the aid of global financial assets.

This study suggests a more accurate prediction model for BTC trading by combining the dynamic conditional correlation generalized autoregressive conditional heteroscedasticity (DCC-GARCH) model with the artificial neural network (ANN). The DCC-GARCH model offers significant input information, including dynamic correlation and volatility, to the ANN. To analyze the data effectively, the study divides it into two periods: before and during the COVID-19 outbreak. Each period is then further divided into a training set and a prediction set.

The empirical results show that BTC and gold have the highest positive correlation compared with crude oil and the USD, while BTC and the USD have a dynamic and negative correlation. More importantly, the ANN-DCC-GARCH model had a cumulative return of 318% before the outbreak of the COVID-19 pandemic and can decrease loss by 50% during the COVID-19 pandemic. Moreover, the risk-averse can turn a loss into a profit of about 20% in 2022.

The empirical analysis provides technical support and decision-making reference for investors and financial institutions to make investment decisions on BTC.

Collective reputation cognition is an enterprise's perception of the general rules of reputation evaluation, jointly formed by a network's collective members. It affects the choice of enterprises' innovation behavior and guides enterprises to occupy a dominant position in the innovation network, thus achieving high innovation performance. In this process, it is inseparable from the enterprise's good network competence. This study attempts to bring collective reputation cognition, network competence and innovation performance into the same framework and aims to explore the relationship among them and determine the influential roles of collective reputation perception and network capability on innovation performance.

This study uses 227 Chinese enterprises in the innovation network as samples and applies partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to explore the questions mentioned above.

The results verify the relationship among collective reputation cognition, network competence and innovation performance. Furthermore, the results yield five paths that lead to high innovation performance, such as “putting ability first” and “both fame and competence”, which are different combinations of collective reputation cognition and network competence.

Based on institutional theory, this study considers the network context and identifies “collective reputation cognition” as a key variable. Meanwhile, it opens the “black box” of the mechanism of reputation's influence on innovation performance and finds that the combined paths of collective reputation cognition and network competence achieve high performance in terms of innovation.

This paper aims to provide a shimming method based on scanned data and finite element analysis (FEA) for a wing box assembly involving non-uniform gaps. The effort of the present work is to deal with gap compensation problem using hybrid shims composed of solid and liquid forms.

First, the assembly gaps of the mating components are calculated based on the scanned surfaces. The local gap region is extracted by the seed point and region growth algorithm from the scattered point cloud. Second, with the constraints of hole margin, gap space and shim specification, the optional shimming schemes are designed by the exhaustive searching method. Finally, the three-dimensional model of the real component is reconstructed based on the reverse engineering techniques, such as section lines and sweeping. Using FEA software ABAQUS, the stress distribution and damage status of the joints under tensile load are obtained for optimal scheme selection.

With the scanned mating surfaces, the non-uniform gaps are digitally evaluated with accurate measurement and good visualization. By filling the hybrid shims in the assembly gaps, the joint structures possess similar load capacity but stronger initial stiffness compared to the custom-shimmed structures.

This method has been tested with the interface data of a wing tip, and the results have shown good efficiency and automation of the shimming process.

The proposed method can decrease the manufacturing cost of shims, shorten the shimming process cycle and improve the assembly efficiency.

The purpose of this article is to develop relationships between many major issues relevant to the agriculture supply chain.

With the purpose of gaining an all-encompassing understanding of the agriculture supply chain, this work uses 233 filtered research articles and three bibliometric analysis tools, namely VOSviewer, term frequency-inverse document frequency (TF-IDF) and Person correlation. The collected research publications were also catalogued using Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA).

Using analytic techniques, a total of 12 keywords were obtained. The study found that agri-products are in dire need of digitisation via Internet of things (IoT) and blockchain due to the usage of economic variables and comprehensive management of total food waste throughout transportation, anchoring quality and the predominant variable.

The study was limited to the Scopus and Web of Science (WoS) indexing in order to assess the viability of the linked idea and problem.

This study aims to generate vital knowledge in the field of horticulture-focused agriculture supply chain based on previous justification and relationship formation.

Most years, several AIB members are elected as AIB Fellows on account of their excellent international business scholarship, and/or past service as AIB President or Executive Secretary. The Fellows are in charge of electing Eminent Scholars as well as the International Executive and International Educator (formerly, Dean) of the Year, who often provide the focus for Plenary Sessions at AIB Conferences. Their history since 1975 covers over half of the span of the AIB and reflects many issues that dominated that period in terms of research themes, progresses and problems, the internationalization of business education and the role of international business in society and around the globe. Like other organizations, the Fellows Group had their ups and downs, successes and failures – and some fun too!

This study aims to explore the relationship between the degree of state-owned enterprises’ (SOEs) mixed reform and the environmental response of enterprises, against the background of actively promoting the reform of mixed ownership in China.

The study is conducted on a sample of A-share listed manufacturing companies in Shanghai and Shenzhen of China, investigated for the period 2015 to 2020. The baseline regression results are robust to a series of robustness and endogeneity tests. To deal with the issue of endogeneity, the technique of instrumental variable method has been applied.

The study confirms the U-shaped effect of the depth and restriction of mixed ownership on SOEs’ environmentally responsive behaviour in the manufacturing industry, especially for lower environmental regulation and higher level of risk-taking firms. The findings indicate that the government, shareholders and other stakeholders of enterprises should not simply consider that the mixed reform is directly promoting or reducing the environmental response behaviour of enterprises.

SOEs should improve their shareholding structures to undermine performance enhancement at the expense of the environment and increase environmentally beneficial behaviours. Regulators and governments should improve the institutional mechanism of environmental regulation and make efforts to promote corporate awareness of the environment.

Although the adoption and implementation of environmentally friendly policies are costly, improved environmental response and other social responsibilities are helpful to corporate long-term growth and reputation and obtain more capital market attention. Therefore, firms would benefit from improving their environmental response to protect nature, as well as to enjoy the economic and social benefits of a better environmental response.

To the best of the authors’ knowledge, there is a lack of studies focussing on the environmental behaviour of SOEs of mixed reform. As the mixed reform in China has come to a climax phase in recent several years, SOEs of mixed reform is an ideal environment for research. The study focusses on manufacturing firms as these firms are more susceptible to contribute to environmental pollution, exploitation of natural resources and labour concerns.

In his autobiography, Chen Shui-bian (1999, p. 40) condemned the Koumintang's (KMT's) corruption and praised the Democratic Progressive Party (DPP) for being free from money politics and corruption. The DPP fought the 1992 Legislative Yuan election campaign effectively on an anticorruption platform and used the same strategy in subsequent elections. If Chen Shui-bian had criticized the KMT for its involvement with “black gold” politics and had won the 2000 presidential election on his anticorruption platform, why was he and his family found guilty of corruption after his second term of office? The short answer is that even though he had promised to curb corruption, President Chen himself had succumbed to corruption after assuming office. In June 2002, Keesing's Contemporary Archives cited a poll in Taiwan that indicated that more respondents had perceived the DPP to be more corrupt than the KMT (Copper, 2006, p. 14).