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The purpose of this paper is to use samples from Chinese-listed companies to investigate the effects of interest rate deregulation and earnings transparency on company’s capital structure in China over the period of 2003–2015. In particular, the authors study the link between state-owned enterprises (SOEs), economic growth targets and marketization in China’s unique institutional context.

Based on the methodology of quantitative analysis, the authors use baseline and cluster analysis for all samples with full set of controls, for robustness tests of alternative proxy of interest rate control by using a cluster analysis at the firm level, regarding endogeneity tests conducted fixed effect model with adding instrument variables (IV), two-period factors regression method via IV and system generalized method of moments for dynamic analysis.

The results show that earnings transparency increases firm leverage and the additional tests suggest that such an effect takes place via a mechanism by reducing the cost of debt finance. However, information transparency could moderate the effects of interest rate deregulation on corporate capital structure. In addition, it finds that SOEs are less sensitive toward the changes of interest rates in China because lending to SOEs is policy-oriented and lacks of market evaluation of business risk. Government control is conducive to enhancing the transparency of the whole industry; however, market-oriented reform is conducive to enhancing the transparency of the company’s own information.

The paper makes contribution to the relationship between earnings disclosure quality and capital structure in the Chinese unique institutional context, such as taking the progressive interest rate reform, SOES, different economic growth target and different marketization level in each province of China. The authors suggest that investors will pay more attention to the company’s own unique information transparency in the provinces with a high degree of marketization. As a potential direction for future research, the authors will investigate how the earnings transparency has impact on capital structure, and how such impact would depend on the transparency of specific business, the cap of foreign shareholding and the convenience of investment.

This research would be the target of banking market reform in order to bring a fair financing environment for all businesses in China. It implies that current experiment of interest rate liberalization in China is not as efficient as it could be in allocating funds across all businesses. State banks, SOEs and local governments are still the biggest players on both the demand and supply sides of the Chinese credit markets.

The social implication of this paper lies in the fact that first, it provides additional evidence on the effect of market-oriented reforms through how the information transparency interacts with the financial decisions making of corporations. Second, it offers policy implication to banking market deregulation in China.

The paper makes contribution to the relationship between earnings disclosure quality and capital structure in the Chinese unique institutional context. This research tests the existing literature, such as Francis et al. (2004) and Zhang and Lu (2007), and suggests that informationally transparent firms have a higher debt ratio and lower effective interest costs on bank loans. In addition, this paper further explores the role played by interest rate deregulation in corporate finance, and in turn market fund allocation. This paper sheds new light on information transparency and explores the relationship between earnings disclosure quality and debt financing behaviors of Chinese publicly listed companies over the period of 2003–2015.

The car-sharing market has entered the mature stage, and consumers' demand shows a diversified increasing trend. This paper considers two modes of operation and two pricing strategies, which are business-to-consumer and consumer-to-consumer modes, market pricing and platform pricing. Under these conditions, the platform's revenue-sharing ratio will be different. The purpose of this paper is to explore this research question, and seeks an optimal pricing mechanism that can achieve a win–win situation between platform and automobile manufacturer in the two market modes.

The authors design different profit functions for platform under the two contexts. Of course, the platform's function is constrained to the manufacturer's function. By introducing a revenue-sharing contract a Stackelberg game model dominated by the platform is established and the equilibrium solutions under the two pricing models are derived.

The study found that even if only market pricing is executed, the scale of the car-sharing market will continue to expand. As the car-sharing market becomes more saturated, platform pricing is better for the automobile manufacturer; in most cases, the platform prefers platform pricing, but when the number of private cars is relatively small, if the cost of car operation and maintenance for the automobile manufacturer is lower or the revenue-sharing ratio of private cars is high, then market pricing will be more favorable to the platform.

With the cross-border integration of car service platforms and the automobile manufacturing industry, the key to achieving win–win cooperation and sustainable development in the car-sharing market will converge on the question of how to design a suitable pricing mechanism and revenue-sharing method.

Authors have determined how a car-sharing platform achieves a win–win order pricing strategy with the manufacturer and private car owners, respectively. And authors combined the supply chain revenue-sharing contract with the car-sharing market to explore the application of the revenue-sharing contract in the sharing economy.

This study, a symposium, aims to explore the determinants of financial inclusion, impact of cross-country income-variations on financial inclusion, do high-income countries really uplift the financial inclusion and does the higher financial inclusion index indicate the larger economy?

This study adopts the panel data model to investigate the impact of high-income countries and low- and middle-income countries on financial inclusion. However, this study further adopts the principal component analysis rather than Sarma’s approach to calculate the financial inclusion index.

Based on the Data of World Bank, United Nations, International Monetary Fund, World Development Indicators, this study concludes that there is no nexus between income variations and financial inclusion, as the study reveals that some low- and middle-income countries have greater financial inclusion index such as Thailand (2.8538FII), Brazil (1.9526FII) and Turkey (0.8582FII). In low- and middle-income countries, the gross domestic product per capita, information technology and communication, the rule of law, age dependency ratio and urbanization have a noteworthy impact on financial inclusion that accumulatively describe the 83% of the model. Whereas, in high-income countries, merely, information technology and urbanization have a substantial influence on the growth of financial revolution and financial inclusion that describes the 70% of the total.

The biggest limitation is the availability of data from different countries.

The originality of this paper is its technique, which is used in this paper to calculate the financial inclusion index. Furthermore, this study contributes to 40 different countries based on income, which could help to boost financial inclusion, and ultimately, it leads them toward economic growth.

This paper attempts to discover whether or not social networks work in the same way in different sectors of the labour market in the same society, using data from the 2008 Asian Social Survey. Labour markets in some societies are segmented; there are two segments in the labour market, namely, the core sector and the peripheral sector. The practices of each sector differs from the others. Some sectors employ CME labour markets, while others favour LME labour markets (Kanbayashi and Takenoshita, 2014). In other words, we can find both CME and LME labour market in one society.

Since Granovetter’s (1973) pioneer study, scholars are interested in investigating in what way social network influence our job searching outcomes. However, these researchers have not yet yielded consistent results. Scholars argue that the institutional context of labour market can shape the network impacts on our job search outcome (Chen, 2014; Chua, 2011).

Surprisingly, this paper finds that there is no room for the use of personal contact in the public sector in both China and Japan. But, mean status is positively related to annual income in the private companies sector in both Japan and China. The significant influences of mean status in the private sectors in both China and Japan reflect the reinforcing of existing social inequality structure. This is because as the status of contact can facilitate respondents' job attainment process, those who are already in higher social status are more likely than those who are in the bottom of the social strata, to get a better job with the help from their network members.

The above findings show us that social network can exert various impacts on people's job searching process even in the same society. This is because it is possible that the labour market are segmented. These segments have very different practices. This difference attributes to the inconsistent findings of network effects on occupational attainment process. Therefore, it is essential to locate which labour market respondents are in, and the features of this labour market. This can help us know more about the use and effectiveness of network in different types of labour markets.

A chaotic system is a nonlinear deterministic system that displays complex, noisy‐like and unpredictable behavior. The interest in chaotic systems lies mostly upon their complex, unpredictable behavior, and extreme sensitivity to initial conditions as well as parameter variations. Based on wavelet neural network's (WNN) online approximation ability, the purpose of this paper is to propose an adaptive Gaussian wavelet neural control (AGWNC) system to control a chaotic system.

The proposed AGWNC system is composed of a wavelet neural controller and a compensation tangent controller. The wavelet neural controller utilizes a Gaussian WNN to mimic an ideal controller, and the compensation tangent controller is designed to compensate the approximation error between the ideal and the wavelet neural controllers. The controller parameters of the proposed AGWNC can online tune in the Lyapunov sense, thus the uniformly ultimately bounded stability of closed‐loop system can be guaranteed.

The proposed AGWNC system is applied to a chaotic system. Simulation results are used to demonstrate the effectiveness and performance of the proposed AGWNC scheme. Simulation results show that not only the favorable control performance can be achieved but also the control efforts without any chattering phenomena. Moreover, all controller parameters can be online tuning by the derived adaptive laws based on the Lyapunov function.

The proposed AGWNC approach is interesting for the design of an intelligent control scheme. The main contributions of this paper are: the overall closed‐loop control system is globally stable in uniform ultimate boundedness; the tracking error can be asymptotically attenuated to a desired small level around zero by appropriate chosen parameters and learning rates; and the AGWNC system can achieve favorable tracking performance.

The utilisation of market-based approaches (MBAs) than command-control approaches (CCAs) is still at the embryonic stage to stimulate the green behaviour of small and medium-sized enterprises (SMEs) in developing economies. The study aims to elucidate the association between environmental incentives (EIs), green responsiveness (GR) and environmental performance (EP).

A quantitative dominant research design is adopted with qualitative support. The study model is developed by integrating legitimacy theory (LT) and the natural resource-based view (NRBV). The cross-sectional data were gathered from the upper echelon of 395 SMEs in Sri Lanka, and 10 subsequent interviews were conducted. The partial least squares approach of structural equation modelling (PLS-SEM) was used to evaluate the hypothesised relationships.

The results found evidence to demonstrate that EIs positively link with GR and EP and GR mediates this association. Further, the study revealed that although MBAs are established, the SME sector is less aware of EIs such as tax concessions, tax reliefs, low interest, soft loans and discounts on eco-materials.

The results provide valuable insights to enhance environmental sustainability. The owners of SMEs should strategically use environmental inducements to overcome resource poverty to engage in green practices. The regulators and policymakers should develop the incentive policies and provide the mechanisms to disseminate the required skills and technologies to SMEs.

According to the authors' best knowledge, this is one of the pioneering empirical studies on EIs, GR and EP with mediating effects in Sri Lanka.

The purpose of this paper is to examine in greater depth the concept of “board capital”, which the authors consider to be a bundle of three types of capital, and believe to be a clear antecedent of the board’s ability to perform its roles, which have positive consequences for the firm’s performance.

Through 83 firms listed on The Madrid Stock Exchange during the period 2005-2010, the authors test empirically the relationships between different dimensions of board capital and firm performance, and specially how internal social capital moderates the relationships between board human capital and external social capital with firm performance.

The results show that certain characteristics of human capital (average board tenure) and external social capital (directors’ interlocks) are positively related to the firm performance. The empirical findings also indicate that the internal social capital, measured by board density, is positively related to the firm performance and moderates these above relationships, increasing the potential of the resources contributed by the board members and influencing to a large extent on a firm’s performance.

The results of the investigation will help both executives and scholar in two ways. First, they will assist firms when they have to select board members, as they can now understand how the resources that board members bring with them can affect the firm performance. To be more effective, boards need to have members that have experience as firm’s directors, external connections to other boards and many internal ties among them. Second, in this context, internal social capital is especially relevant, so the firms should look for possible ways of encouraging internal ties between directors. In this paper, the authors have opted for study the participation of directors in committees.

The authors propose that these three types of capital (human, external and internal social capital) need to be synergistically combined to create a group of directors with access to a complete set of skills, knowledge and connections, but which can still work as a compact social group when making decisions.

The detection of an adversary in secret image sharing has been a problematic side in the reconstruction phase. Some of verifiable secret sharing solutions have been proposed to solve the problem. However, there is some computational limitation in the previous schemes. The purpose of this paper is to analyze the importance of consistency for detecting an adversary in a secure reconstruction phase. Strong t-consistency assures the correctness of reconstructed secret as long as participants P ∈ N and n(P) = t. Consistency is a solution for preventing the participant to be absent and helps the dealer to easily detect the adversary without an additional verification step.

This paper focuses on secure reconstruction, and uses two different approaches, namely, single-secret and multi-secret, to experiment the relationship between the given variable (t,m,n) and the adversaries by observing the quality test result, polynomial approach and visualization.

The results show that t and m are inversely proportional to the image quality without respect to the polynomial approach. The reconstruction phase is declared as securely conducted when m = 2t − 1, for both single- and multi-secret approaches.

The application of consistency is a considerable step for securing the secret from an adversary by combining the reconstruction phase and the consistency combination at once, removing the need for additional separate verification steps for decreasing the computational time, especially in secret image sharing.

This study aims to compare the short-run performance of construction and non-construction initial public offerings (IPOs) that are offered in India during 2006–2015. The study also attempts to investigate the impact of ownership structure (i.e. concentrated ownership in the hand of promoters and institutional ownership) and market sentiment on the performance of construction sector IPOs in short run.

A total of 281 IPOs were listed at National Stock Exchange, India, during the study period, and 44 of those were from construction sector. The short-run performance of these construction and non-construction IPOs was compared using two indicators, i.e. monthly stock return (SR) and excess return over market benchmark (MAR). To examine the effect of concentrated ownership in the hand of promoters, institutional ownership and market sentiment on IPO performance, systematic dynamic panel regression model was developed.

The IPOs of construction firms perform significantly better than the non-construction firms. The performance of construction IPOs is significantly driven by the lag effect. This suggests a significant informational inefficiency, which results in a delayed reaction by investors. The market sentiment has a positive influence on the performance of construction sector IPOs, whereas the institutional holding has a negative influence.

To the best of the author’s knowledge, this study is the first attempt to examine the performance of construction sector IPOs in short run. The study uses systematic dynamic panel data regression, which provides better and reliable estimates.

Due to social transformation in China, more than 100,000,000 people are migrating within the country. Many parents are forced to leave their children behind when they migrate. In 2008, 58,000,000 children were living as left‐behind children, mainly in the rural parts of China (Zhang, 2009).Migration and its accompanying stressors may affect the mental health of the left‐behind children. This unique literature review of Chinese literature summarises the present state of knowledge and reviews the influential factors. Possible approaches to intervention and system reforms are discussed.A literature review was performed of published studies between 2001 and 2008. Databases used were Fujian Medical University Library Interface, Chinese National Knowledge Infrastructure, Wanfang Data, and VIP Information. The Chinese word for ‘left‐behind’ was used as a key word. Books, book chapters, monographs and studies on caring were searched electronically and by hand. Altogether, 53 items were found, discussed and grouped together. Migration affected the mental health of the left‐behind children in a passive way, especially their emotions and social behaviour.There is still controversy over how serious mental health problems are among children who have been left behind. Life events, personality, coping strategies and social suppor t can be regarded as four main factors that are predictive of mental health, which provides theoretical guidance for intervention. Suppor t and prevention of mental health problems in schools, in families and in primary care should be developed and studied.