Search results

Several multivariate statistical methods were comprehensively used to interpret the temporal, spatial patterns and source identification of surface water pollution in Bohai Bay with the large and complex data. Twelve variables water quality indices were surveyed at 12 sites three times a year (May, August, and October) from 1995 to 2005. Cluster analysis (CA) grouped the eleven years into two clusters, Cluster A (1995 to 2001 except 1998) and cluster B (2002 to 2005 and 1998), and spatial CA divided the entire area into three groups. The results of discriminant analysis showed that the temporal CA and spatial CA were effective with 90% and 83.3% correct assignments, respectively. In cluster A, the pollution sources mainly were nutrient factor from non-point source and Hg pollution, oil and organic pollutions were relatively light. In Cluster B, the organic pollution became the mainly pollution source, and the nutrient pollution was still serious problem. In the results of spatial analysis, the group 1 was mainly affected by anthropogenic pollution, the group 3 was seriously affected by oil spill pollution and nutrients pollution, and the group 2 reflected relatively strong water self-purification ability.

This paper aims to investigate how perceived working conditions affect employee performance, including safety compliance and task performance, through employee well-being (i.e. job satisfaction) in the context of the coal mining sector in China.

This paper uses the job demands-resources model to test the relationships between working conditions, including job demands (work pressure as a challenge demand and perceived risks and hazards in the workplace and ineffectiveness of the safety system as hindrance demands), job resources (interpersonal harmony), job satisfaction and performance. This study adopts a two-wave design with a three-month lag to reduce possible common method bias.

Employees who experienced high level of challenge demands, e.g. time pressure workload, reported higher levels of task performance, and this positive relationship seemed to be robust. There is a direct effect of perceived ineffectiveness of the safety system on task performance, while the relationship between perceived risks and hazards and task performance was fully mediated by job satisfaction. Challenge demands, i.e. work pressure, did not impact much on employees’ well-being, and thus job satisfaction did not mediate the relationship between work pressure and performance. Perceived ineffectiveness of the safety system was negatively associated with safety compliance. This result is not surprising since a lack of effective safety system reflects management’s ignorance of workplace safety, which demotivates employees to enact safe behaviors. In contrast, the presence and implementation of an effective safety system would be interpreted by employees as management exhibiting a high level of commitment. Work pressure was positively not negatively related to safety compliance. One possible explanation for this finding is that the effects of work pressure on safety compliance behaviors might be dependent on contextual factors such as safety climate. Interpersonal harmony moderated the relationships between work pressure and employee performance (both safety compliance and task performance) and the relationship between perceived risks and hazards and task performance, but the role of interpersonal harmony appeared more complex. There was no significant correlation between challenging job demands and individual employee performance when there were higher levels of interpersonal harmony. The relationship between perceived risks and hazards, a hindrance job demand and task performance became positive as interpersonal harmony increased but negative as interpersonal harmony decreased.

This paper provides a robust integrative theoretical framework that better explains the various types of job demands and job resources in the working environment of coal mining sector in China and their relationships to employee performance. The findings also offer valuable guidance for managers trying to identify effective ways to enhance employee performance and safety in the workplace.

Entrepreneurship.

This case is suitable for MBA, EMBA and advanced undergraduate students.

Noah Wealth Management was founded by Ms Wang Jingbo, a lady in her mid 30s with a team of less than 20 members in 2005. Exploiting market opportunities offered by a lack of good wealth management products and services, Noah grew rapidly from one branch office in 2005 to 59 branch offices in 2011, reaching a staff size of 1,031. Noah listed its shares on the New York Stock Exchange in November 2010. In 2011, Noah was ranked No. 38 among the 100 Top Potential Enterprises in China. Nonetheless, Noah faced several problems of internal management during the course of its fast expansion. In the first quarter financial report of 2012, Noah suffered a 52.6 percent decrease in net income over the corresponding period in 2011. Faced with a rapidly declining share price, Noah announced on May 22, 2012 a US $30 million share repurchase program.

The case supports a basic lesson on the entrepreneurial cycle, including assessing a business opportunity, resource mobilization, identifying a business model, growth of the venture, listing on the stock market, and subsequent growth challenges. Students can learn about some of the typical dilemmas faced by founders of entrepreneurial ventures, including how to maintain the corporate culture while growing fast and how to prevent members of the founding team from becoming bottlenecks to the development of the organization. The case can also provide management students with an overview of China's wealth management industry.

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

This paper aims to unravel the technological innovation pattern in China’s aerospace industry. The technological innovation pattern of China’s aerospace industry is identified and its theoretical foundation, structure, philosophy, formation and effects on the development of China’s aerospace industry are explored.

First, the theoretical foundation of synergy innovation of China’s aerospace industry is reviewed to further identify the technological innovation pattern. Second, Chinese ancient philosophy (dialectical thinking) is used to explain the structure and process of synergy innovation in China’s aerospace industry. Third, the formation process of synergy innovation is introduced, and, finally, the effects of synergy innovation are discussed.

The technological innovation pattern of China’s aerospace industry has undergone an evolutionary process. During this process, China’s aerospace firms have formed a unique technological innovation pattern, synergy innovation, under China’s special political and economic background. The synergy innovation has three characteristics, including original, integrated and application-based. The synergy innovation pattern application is one of the most important reasons behind the great achievements of China’s aerospace industry.

A unique technological innovation pattern, synergy innovation, is proposed for the first time. A new perspective for understanding innovation is provided by applying the Chinese dialectical thinking to decipher the philosophy of the technological innovation pattern. Based on this, this paper suggests that China’s aerospace industry should follow the situation and apply the synergy innovation pattern to achieve development and growth. This paper also illustrates a multi-method approach and emphasizes the different levels of organizing for innovation.

Smart manufacturing is the prime gripper for the transformation and upgrading of the manufacturing industry. Smart manufacturing systems (SMSs) largely determine how smart manufacturing evolves in technical and organizational dimensions and how it realizes values in products, production or services. SMSs are growing rapidly and receiving tons of attention from academic research and industrial practice. However, the development of SMSs is still in its fancy, and many issues wait to be identified and solved, such as single point failures, low transparency and ineffective resource sharing. Blockchain, an emerging technology deriving from Bitcoin, is competent to aid SMSs to conquer troubles due to its decentralization, traceability, trackability, disintermediation, auditability and etc. The purpose of this paper is to investigate the blockchain applications in SMSs, seek out the challenges faced by blockchain-enabled SMSs (BSMSs) and provide referable research directions and ideas.

A comprehensive literature review as a survey is conducted in this paper. The survey starts by introducing blockchain concepts, followed by the descriptions of a literature review method and the blockchain applications throughout the product life cycle in SMSs. Then, the key issues and challenges confronting BSMSs are discussed and some possible research directions are also proposed. It finally presents qualitative and quantitative descriptions of BSMSs, along with some conclusions and implications.

The findings of this paper present a deep understanding about the current status and challenges of blockchain adoption in SMSs. Furthermore, this paper provides a brand new thinking for future research.

This paper minutely analyzes the impacts that blockchain exerts on SMSs in view of the product life cycle, and proposes using the complexity science thinking to deal with BSMSs qualitatively and quantitatively, including tackling the current major problems BSMSs face. This research can serve as a foundation for future theoretical studies and enterprise practice.

This paper aims to introduce corporate social responsibility into the green supply chain and analyse the impact of different decision makers’ decision-making schemes on carbon emission reduction in the supply chain.

This study uses a two-stage low-carbon supply chain composed of a manufacturer and retailer as the research object. It uses the Stackelberg game model to analyse optimal carbon emission reduction and its influence under different decision-making modes.

Increased consumer green preferences and trust can improve the manufacturing enterprises’ carbon emission reduction rate. The carbon emission reduction rate decreases with increased green innovation costs. When green technology innovation costs remain constant, the greater the market capacity, the higher the carbon emission reduction rate. Market capacity has the most significant impact on the optimal carbon emission reduction rate without considering social responsibility decisions and has the least impact on the optimal carbon emission reduction rate while fully considering the social responsibility decision. To achieve decarbonisation production, the market capacity must be small, and when green innovation costs are high, it is the optimal choice without considering social responsibility. To achieve a higher level of carbon emission reduction, when the market capacity is low and the research and development cost is high or when the market capacity is large, it is the optimal choice.

The results provide scientific policy decisions and management significance for governments and enterprises in low-carbon subsidies and supply chain management. The findings also provide a basis for future theoretical research and enterprise practice.

Examines the tenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

Examines the ninth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

This paper aims to illustrate the tolerance optimization method based on the assembly accuracy constrain, precession constrain and the cost of production of the assembly product.

A tolerance optimization method is an excellent way to perform product assembly performance. The tolerance optimization method is adapted to the process analysis of the hatch and skin of an aircraft. In this paper, the tolerance optimization techniques are applied to the tolerance allocation for step difference analysis (example: step difference between aircraft cabin door and fuselage outer skin). First, a mathematical model is described to understand the relationship between manufacturing cost and tolerance cost. Second, the penalty function method is applied to form a new equation for tolerance optimization. Finally, MATLAB software is used to calculate 170 loops iteration to understand the efficiency of the new equation for tolerance optimization.

The tolerance optimization method is based on the assembly accuracy constrain, machinery constrain and the cost of production of the assembly product. The main finding of this paper is the lowest assembly and lowest production costs that met the product tolerance specification.

This paper illustrated an efficient method of tolerance allocation for products assembly. After 170 loops iterations, it founds that the results very close to the original required tolerance. But it can easily say that the different number of loops iterations may have a different result. But optimization result must be approximate to the original tolerance requirements.

It is evident from Table 4 that the tolerance of the closed loop is 1.3999 after the tolerance distribution is completed, which is less than and very close to the original tolerance of 1.40; the machining precision constraint of the outer skin of the cabin door and the fuselage is satisfied, and the assembly precision constraint of the closed loop is satisfied.

The research may support further research studies to minimize cost tolerance allocation using tolerance cost optimization techniques, which must meet the given constrain accuracy for assembly products.

This paper aims to present an adaptive sliding mode control (ASMC) for tunnel boring machine cutterhead telescopic system with uncertainties to achieve a high-precision trajectory in complex strata. This method could be applied to solve the problems caused by linear and nonlinear model uncertainties.

First, an integral-type sliding surface is defined to reduce the static tracking error. Second, a projection type adaptation law is designed to approximate the linear and nonlinear redefined parameters of the electrohydraulic system. Third, a nonlinear robust term with a continuous approximation function is presented for handling load force uncertainty and reducing sliding mode chattering. Moreover, Lyapunov theory is applied to guarantee the stability of the closed-loop system. Finally, the effectiveness of the proposed controller is proved by comparative experiments on a scaled test rig.

The linear and nonlinear model uncertainties lead to large variations in the dynamics of the mechanism and the tracking error. To achieve precise position tracking, an adaptation law was integrated into the sliding mode control which compensated for model uncertainties. Besides, the inherent sliding mode chattering was reduced by a continuous approximation function, while load force uncertainty was solved by a nonlinear robust feedback. Therefore, a novel ASMC for tunnel boring machine cutterhead telescopic system with uncertainties can improve its tracking precision and reduce the sliding mode chattering.

To the best of the authors’ knowledge, the ASMC is proposed for the first time to control the tunnel boring machine cutterhead telescopic system with uncertainties. The presented control is effective not only in control accuracy but also in parameter uncertainty.