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Since the multi-component of powder metallurgy was dispersed, and each component sheared flow and tiered under the action of friction force, it was difficult to disclose the evolution characteristics of each component. Meanwhile, third body mixing with particles of each component covered on the friction surface, which further increased the difficulty of understanding evolution of each component and the corresponding third body in the friction process. To solve this problem, this paper aims to propose a mechanical assembled method which compact several component sheets in order.

Pure copper, aluminum and artificial graphite sheets with thickness 0.5, 1 and 2 mm, respectively, were assembled into a jig by mechanical compact method. The relationship between arrangement patterns of the components and its friction coefficient was studied by using fixed speed friction test machine, the speed range from 200 to 2,000 r/min and the pressure range from 0.25 to 0.64 MPa.

The testing results showed that when the distribution of same components was congregated, friction coefficient dropped from 0.6 to 0.4. While the distribution of different components was dispersed, friction coefficient dropped from 0.6 to 0.25. The friction coefficient decline was caused by performances changes of third body fluidity. The sufficiently mixed third body made third body adhesion weaker and increased third body fluidity. That provoked friction coefficient decreasing obviously at high speed. On the contrary, with the high congregation of same components, strong third body adhesion led to a rougher surface which contributed to a higher friction coefficient.

By means of the mechanical-assembled multi-layer components to reveal the influence mechanism of every component on friction properties, will provide a new test approach for tribology.

The purpose of this research is to provide a systematic insight into corporate social responsibility (CSR) and corporate citizenship (CC) in supply chain development, by analyzing the current literature, contemporary concepts, data and gaps for future discipline research.

This research identifies information from existing academic journals and investigates research designs and methods, data analysis techniques, industry involvement and geographic locations. Information regarding university affiliation, publishers, authors, year of publication is also documented. A collection of online databases from 2001 to 2018 were explored, using the keywords “corporate social responsibility”, “corporate citizenship” and “supply chain” in their title and abstract, to deliver an inclusive listing of journal articles in this discipline area. Based on this approach, a total of 164 articles were found, and information on a chain of variables was collected.

There has been visible growth in published articles over the last 18 years regarding supply chain sustainability, CSR and CC. Analysis of the data collected shows that only five literature reviews have been published in this area. Further, key findings include 41% of publications were narrowly focused on four sectors of industry, leaving gaps in the research. 85% centered on the survey and conceptual model, leaving an additional gap for future research. Finally, developing and developed nation status should be delineated, researched and analyzed based on further segmentation of the industry by region.

This research is limited to reviewing only academic and professional articles available from Emerald, Elsevier, Wiley, Sage, Taylor and Francis, Springer, Scopus, JSTOR and EBSCO containing the words “corporate social responsibility”, “corporate citizenship” and “supply chain” in the title and abstract.

This assessment provides an enhanced appreciation of the current practices of current research and offers further directions within the CSR and CC in supply chain sustainable development.

With the worldwide growth of the Chinese tourism market, a number of studies have emerged, that attempt to understand the phenomenon, including the influence of Chinese culture on Chinese tourist behavior. This research aims to answer four questions: How has Chinese culture been adopted in tourism literature? What is the current state of tourism research on Chinese culture? What are the similarities, differences and research gaps between international and Chinese studies in this area of investigation? What are the directions that future tourism research will take?

The articles for this systematic review were published in major international hospitality and tourism journals and Chinese journals over a period of 20 years (1993-2012). A meta-review was carried out on 80 Chinese and English tourism literature dating from 1993 to 2012.

This review showed that Chinese culture has been fragmentally operationalized due to underdeveloped Chinese cultural theories in tourism, independent and unrelated extant cultural systems and perspectives and lack of empirical testing for theory development. Two major theoretical systems of Chinese culture in tourist research were revealed in this review: cross-cultural theory and traditional Chinese cultural framework. The current state of tourism research on Chinese culture was also analyzed. The similarities, differences and research gaps were identified between international and Chinese studies on this inquiry. Implications for future tourism research in this area were suggested.

Unveiling the evolving research progress of a single culture helps to provide a deeper insight into how culture was used to analyze the behavior of individual tourist markets, and hence to better understand a particular tourist market.

This research has synthesized a wide range of literature to unveil the extant understanding of Chinese culture as reflected in Chinese tourists and outline the ways forward in this area of investigation.

China has long been dedicated to introducing the Western management ideas to the local enterprise practice. But the situation has changed since the financial crisis, and the China model has become a hot word with its fast recovery from crisis. Moreover, Chinese traditional culture has become increasingly popular. Yin and yang are the most familiar Chinese philosophical terms to Western minds, and also the core concept of Chinese Taoist philosophy. The purpose of this paper is to analyze how the yin yang or lao‐tzu influences a firm's core competence and performance, and to demonstrate that the Taoist‐oriented Chinese culture remains meaningful and in many situations powerful in enterprise practice.

A case study is carried out from Town Star Ltd, established in 2001, and located in Linfen city, Shanxi province, China, a city which topped the list of the world's most polluted cities. It is an integrated joint‐stock company, specializing in coal coking chemical industry, gardening, logistics and technology development. Based on the humanized management doctrine, the company has formed the 5S management model which boosts its rapid and sustainable development. It coped well in major junctures such as industry restructuring and transferring, financial crisis, etc. Five key dimensions of the yin and yang, which were applied to the leader's daily behaviors and management style, are: Wu‐wei (inaction), Wu (emptiness), hardness with softness, moderation and He‐xie (harmony). First, this paper built a dynamic company growth model based on this philosophy which enhanced the core competitiveness effectively by emotional management innovation and personalized HRM, among which its pivotal regulator of variables is just yin yang conversion degree. Then an approach is provided to validate the model with empirical data collected from the years 2001‐2010 (2001‐2005, 2006‐2008, 2009‐2010) of Town Star Ltd.

It is demonstrated that yin yang ideology embedded in the company growth model organically is an important means to increase marginal benefit. In practice, the firm with yin yang philosophical ideology would shape a management paradigm which combined rules and human nature appropriately to a family‐oriented business atmosphere. Based on the above philosophical wisdom, Town Star Ltd has harvested good economic and social benefits, strong core competence through the elaborately constructed unique management model and harmonious humanity environment.

This paper opens an avenue for indigenous firms, as a framework for guiding management research and practice in coping with the post‐crisis era. In addition, it is expected to attract more attention from scholars, entrepreneurs both in China and in the rest of the world, to contribute to knowledge creation in Chinese management studies.

This paper analyzes the connection between the sustainability performance of Chinese banks and their financial indicators to explore whether sustainability regulations can be implemented without decreasing the financial performance of the banking sector.

The study examined reports and websites of Chinese banks, categorized different corporate sustainability aspects and conducted panel regression and Granger causality to analyze cause and effect variables.

The environmental and social performance of Chinese banks increased significantly between 2009 and 2013. Furthermore, a bi-directional causality between financial performance and sustainability performance of Chinese banks has been found. Based on institutional theory, this interaction may be influenced by the Chinese Green Credit Policy.

The findings suggest that corporate sustainability performance and financial performance are not a trade-off but correlate positively. Further research is needed to analyze the effect of financial regulations, such as the Chinese Green Credit Policy.

According to the good management theory by Waddock and Graves (1997) that claims a positive impact of corporate social performance on financial performance, Chinese banks can invest in corporate sustainability to increase their financial success and re-invest parts of the additional returns – also called slack resources – in sustainability activities.

Chinese banks are able to influence the economy to become greener and less polluting without sacrificing financial returns.

This is the first study to explore the sustainability performance of Chinese banks, including their products and services.

The purpose of this study is to develop and test a theoretical model that accounts for an individual's we-intention to continue playing a mobile multiplayer game.

Drawing on habit-intention and habit formation theories, this study conceptualizes social play habit as a determinant of the we-intention to continue playing and identifies its antecedents. The proposed model was tested through a survey of 277 players of Honor of Kings, a popular mobile multiplayer game.

The results indicate that developing social play habit is critical to the formation of a we-intention to continue playing in the context of mobile multiplayer games. The results also suggest that technological (social features embedded in the game) and individual (desire for co-play and privacy concerns) factors jointly influence social play habit.

This study contributes to the literature on we-intention by conceptualizing social play habit and verifying its role in facilitating a shared intention to continue playing mobile multiplayer games. Our work responds to the call for understanding the mechanism by which multiple people form a shared intention to continue using an information technology at a collective level. Our findings provide significant insights into the design of information technologies for collaboration.

This study is among the first to extend the literature on gaming habits by considering other players' involvement. Specifically, our study shifts researchers' attention from gaming habits characterized by individual properties to social gaming habits characterized by communal properties.

Not all apps can be favored on a smartphone. Users are bound to abandon some if they lose value. Analyzing the reasons behind this phenomenon can help develop strategies for avoiding app abandonment, which is the focus of this study.

This study conducted in-depth open interviews with 47 respondents who had abandoned or deleted mobile apps before and used the qualitative research method grounded theory to analyze the interview content, followed by open coding, axial coding and selective coding.

Seven main reasons are summarized after the relationship between every statement and concept is found and constructed, namely functional value, information expectation, emotional value, platform service, user trust, cost, and social influence.

Based on these findings, this study provided suggestions for mobile app developers to help them effectively improve the user experience and retain their customers.

This work can be used as a building block in other settings such as GPU, Map-Reduce, Spark or any other. Also, DDPML can be deployed on other distributed systems such as P2P networks, clusters, clouds computing or other technologies.

In the age of Big Data, all companies want to benefit from large amounts of data. These data can help them understand their internal and external environment and anticipate associated phenomena, as the data turn into knowledge that can be used for prediction later. Thus, this knowledge becomes a great asset in companies' hands. This is precisely the objective of data mining. But with the production of a large amount of data and knowledge at a faster pace, the authors are now talking about Big Data mining. For this reason, the authors’ proposed works mainly aim at solving the problem of volume, veracity, validity and velocity when classifying Big Data using distributed and parallel processing techniques. So, the problem that the authors are raising in this work is how the authors can make machine learning algorithms work in a distributed and parallel way at the same time without losing the accuracy of classification results. To solve this problem, the authors propose a system called Dynamic Distributed and Parallel Machine Learning (DDPML) algorithms. To build it, the authors divided their work into two parts. In the first, the authors propose a distributed architecture that is controlled by Map-Reduce algorithm which in turn depends on random sampling technique. So, the distributed architecture that the authors designed is specially directed to handle big data processing that operates in a coherent and efficient manner with the sampling strategy proposed in this work. This architecture also helps the authors to actually verify the classification results obtained using the representative learning base (RLB). In the second part, the authors have extracted the representative learning base by sampling at two levels using the stratified random sampling method. This sampling method is also applied to extract the shared learning base (SLB) and the partial learning base for the first level (PLBL1) and the partial learning base for the second level (PLBL2). The experimental results show the efficiency of our solution that the authors provided without significant loss of the classification results. Thus, in practical terms, the system DDPML is generally dedicated to big data mining processing, and works effectively in distributed systems with a simple structure, such as client-server networks.

The authors got very satisfactory classification results.

DDPML system is specially designed to smoothly handle big data mining classification.