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Specimens of 304 stainless steel with various martensite contents were prepared by a low temperature (−70°C) elongation method. Optical microscopy and transmission electron micrography were used to study the phase structure of the samples. A simulated occluded cell (OC) and electrochemical impedance spectroscopy were used to study the chemical and the electrochemical changes within pits on 304 stainless steel containing the different martensite contents. The EIS results showed that the martensite phase decreased not only the solution resistance in pit, but also the polarization resistance value between metal and solution in pit. The composition of the passive film in OC solution was studied by X‐ray photoelectron spectroscopy. It was observed that martensite transformation was a very important factor in changing the composition of the passive film. The martensite phase destroyed the integrality and compactness of the passive film. For these reasons, pit propagation in Type 304 stainless steel was accelerated with increasing martensite content.

The present study is concerned with the application of a nonlinear frequency analysis approach to the detection and location of water tree degradation of power cable XLPE insulation without turning off electric power.

The use of power cable system responses to power line carrier signals are proposed to conduct the required signal analysis for damage location purpose. This technique is based on the fact that the water tree degradation in power cables can make the system behave nonlinearly. Consequently, the location of water tree degradation can be determined by detecting the position of nonlinear components in power cable systems.

A novel method has been proposed for locating water tree degradation in power cable systems; numerical simulation studies have demonstrated the effectiveness of the new technique.

The proposed technique has the potential to be applied in practice to more effectively resolve the power cable damage location problem.

The purposes of this paper are 1) to develop model of long term financial health for logistics companies in Thailand 2) to identify factors that determine long term financial stability. Many researchers currently provide factors affecting financial health. Most factors refer to financial ratios, not many non-financial ratios such as age and size have been mentioned. This paper considers both financial and non-financial ratios that affect financial performance of Logistics companies in Thailand. The study has covered some interesting non-financial ratios such as Nationality of Shareholders, type of network in Logistics Company, growth rate (consisted of sales growth rate/profit growth rate/asset growth rate / Liability growth rate) and variable of growth rates. The target group is 110 logistics companies in Thailand enlisted from Department of International Trade Promotion Ministry of Commerce, Royal Thai Government. The group is divided into three categories according to financial health of company; Healthy financial, Unhealthy (Distress) and normal situation. The Multidiscriminant Analysis (MDA) is applied to analyze the differentiations among the three categories. Significant variables from MDA will be used as the independent variables for Multimonial Logistic Regression Analysis (MLRA) to identify factors that determine long terms financial stability. This paper find CF/D, RE/TA, BE/TL, Size, Age, Type of network, Nationality of Shareholders and Number of Shareholders are significant factors determine long term financial stability of Logistics company in Thailand.

The purpose of this paper is to: first, divide external knowledge into different levels and understand how these different levels of external knowledge create different knowledge networks. Second, explore the relation among different levels of external knowledge, different types of knowledge and their influences on innovation. Different types of knowledge may act as mediators between different levels of external knowledge and innovation performance are also discussed. Third, further explicate the possible reasons behind the phenomena observed in the first and second objectives.

The quantitative and qualitative research methods were adopted in this study. In terms of the quantitative research method, data were collected from 157 information and communications technology (ICT) companies in Zhangjiang. There were 38 interviews carried out using the qualitative research method. Interviewees included 26 directors from the Zhangjiang ICT chip companies and 12 directors from China’s domestic mobile phone manufacturing sector.

This study finds out that the source of external knowledge in the Zhangjiang Hi-Tech Park is mostly derived from cross-regional and cross-national connections. Through the connection with global companies, the firms in Zhangjiang acquire technical knowledge. Also, through the interaction with cross-regional companies, the firms in Zhangjiang absorb market knowledge. The results of this study indicate that the cross-regional connections are spurred by the increasing demand of the Chinese domestic market and the government’s support for cross-regional interactions. Cross-national connections are encouraged and led by the Chinese Government after China’s 3G communication standard is adopted.

This study is built upon a case study in Zhangjiang of China. The findings of this study may not be applicable to other countries or regions in China. Also, this study only focusses on the ICT industry in Zhangjiang. Knowledge from different industries is not included in this study. In addition, the formal and informal knowledge flow is neglected in this study as well.

The findings of this study provide business executives and policymakers with a new way of thinking about the development of industrial clusters and local firms. Firms may be able to find new ways to raise innovation performance using different external knowledge.

The major contribution of this study is an initial attempt to provide a comprehensive analysis of external knowledge of industrial clusters, different types of knowledge and their influences on innovation performance. Moreover, the mediating effects of different types of knowledge are also discussed.

This paper is written as an attempt to employ the Chinese Social Science Citation Index (CSSCI) in the evaluation of Chinese humanities and social science research.

This paper uses statistics in the CSSCI (2000‐2004) to analyze the academic impact of researchers, papers and works, institutions and regions on Chinese humanities and social science research.

The authors identify 100 highly cited people, 50 highly cited papers, 50 highly cited works, 20 highly productive institutions and 20 highly cited institutions. Also provided is some regional information about Chinese humanities and social science research.

It is hoped that the CSSCI, as well as the analysis and evaluation based on it, will give researchers a better understanding of Chinese humanities and social science research.

As a crucial institutional form established since the Chinese economic reform, the system of competitive local governments has been shaping the characteristics of China's socialist market economy to a considerable degree.

This study not only adopts the view of existing studies that attribute the economic motive of local governments to rent and consider land public finance as a means through which local governments carry out strategic investment but also attempts to further develop the view within a Marxist analytical framework.

As a result, the local governments have helped to maintain an incredibly high investment rate over a considerable period of time, facilitating the continuous, rapid growth of the Chinese economy.

This study concludes that China's local governments function as the productive allocator and user of rent in the strategic investment based on land public finance and thereby embed themselves in the relative surplus-value production initially arising from competition amongst enterprises, forming the dual structure of relative surplus-value production unique to China's economy.

External knowledge should not be limited in one zone or level. Researchers have paid more attention to the perspective of multilevel cluster networks. However, little research has empirically studied the various dimensions of external knowledge. The purpose of this paper is to study different levels of external knowledge, their relation with trade and non-trade interdependence and their relation with different kinds of innovations, namely, exploitation and exploration.

Both quantitative and qualitative research methods were adopted in this study. In terms of the quantitative research method, data were collected from 168 companies in the Shenzhen Hi-Tech Industrial Park of China using convenience sampling. As for the qualitative research method, a total of 35 interviews were carried out in this study.

The quantitative results indicate that different levels of external knowledge in the Shenzhen Hi-Tech Park have different effects. First of all, the results indicate that cross-national connections have a positive influence on trade interdependence, which helps firms to produce exploration. Second, cross-regional connections have a positive influence on both trade and non-trade interdependence, which further help firms to create innovative exploitation and exploration. Third, inter-regional connections have a positive influence on non-trade interdependence, which helps firms to increase innovative exploitation. The qualitative result makes a plausible explanation for the quantitative results. The interview results indicate that as the telecommunications industry has so much to do with China’s national security, there are several initiatives of market protection strategies and political interventions, which help firms to form different levels of knowledge flow in Shenzhen.

There are several limitations of this study which primarily relate to the case study method. The results can be contextually generalized to the domestic-oriented cluster in developing countries.

This study has several managerial implications. First, this research ensures that it is important to consider the multilevel nature of external knowledge before starting with the decision-making process of a firm in a cluster. Second, all levels of administrators and managers in a company should investigate what kinds of involvement and innovation are needed and most highly valued for organizational development. Third, the research framework of this study can be applied to understand which level of external knowledge influences organizational performance.

This study is an initial attempt to provide an examination of external knowledge, organizational involvement and innovation performance of an industrial cluster via a mixed method.

Purpose – Criminal groups have long been central to explanations of crime and deviance. Yet, challenges in measuring their dynamic and transient nature meant that group-level explanations were often displaced in favor of individual-level ones. This chapter outlines how network methods provide a powerful tool for modeling the dynamic nature of criminal groups.

Approach – The chapter starts by providing a brief introduction to social network analysis, including key concepts and terminology. The chapter then focuses on the types of relational data available to study criminal groups, and how network methods can be used to delineate group boundaries. The chapter concludes by presenting a framework for understanding group dynamics from a network perspective, describing the contributions of network analysis to theories of group processes.

Findings – Network methods have provided meaningful advances to the study of group dynamics, leading scholars to revisit assumptions about the impact of group’ structure on delinquent behavior. Network studies of group dynamics have primarily focused on the cohesion–delinquency link (within-group structure) and the social contagion of conflict (between-group structure), highlighting important opportunities for the intersection of these two inquiries.

Value – Network methods provide a means to revisit and extend theories of crime and delinquency with a focus on social structure. The unique affinity between group dynamics and network methods highlights immense opportunities for expanding the knowledge of collective trajectories.

In order to solve the current imbalance of academic resources within the discipline, this article builds a three-dimensional talent evaluation model based on the topic–author–citation based on the z index and proposes the ZAS index to evaluate scholars on different research topics within the discipline.

Based on the sample data of the CSSCI journals in the discipline of physical education in the past five years, the keywords were classified into 13 categories of research topics including female sports. The ZAS index of scholars on topic of female sports and so on was calculated, and quantitative indexes such as h index p index and z index were calculated. Comparative analysis of the evaluation effect was performed.

It is found that compared with the h index and p index, the z index achieves a better balance between the quantity, quality and citation distribution of scholars' results and effectively recognizes that the citation quality is higher and the number of citations of each paper is more balanced. In addition, compared to the z index, this article is based on a ZAS index model with an improved three-dimensional topic–author–citation relationship in research fields such as female sports.

It can identify some outstanding scholars who are engaged in small-scale or emerging topic research such as female sports and are excellent in different research areas. Talents create an objective and fair evaluation environment. At the same time, the ranking ability of ZAS indicators in the evaluation of talents is the strongest, and it is expected to be used in practical evaluations.