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With the presence of pricing errors, the authors consider statistical inference on the variance risk premium (VRP) and the associated implied variance, constructed from the option prices and the historic returns.

The authors propose a nonparametric kernel smoothing approach that removes the adverse effects of pricing errors and leads to consistent estimation for both the implied variance and the VRP. The asymptotic distributions of the proposed VRP estimator are developed under three asymptotic regimes regarding the relative sample sizes between the option data and historic return data.

This study reveals that existing methods for estimating the implied variance are adversely affected by pricing errors in the option prices, which causes the estimators for VRP statistically inconsistent. By analyzing the S&P 500 option and return data, it demonstrates that, compared with other implied variance and VRP estimators, the proposed implied variance and VRP estimators are more significant variables in explaining variations in the excess S&P 500 returns, and the proposed VRP estimates have the smallest out-of-sample forecasting root mean squared error.

This study contributes to the estimation of the implied variance and the VRP and helps in the predictions of future realized variance and equity premium.

This study is the first to propose consistent estimations for the implied variance and the VRP with the presence of option pricing errors.

This study aims to examine the behaviour of institutional and retail investors in response to news about industry leaders (peer firms) and to determine its impact on the stock prices of other firms (focal firms) within the same industry.

The study investigates the impact of peer news on investor behaviour of Chinese A-shares listed on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2019. The media coverage of industry leaders is sourced from prominent Chinese online financial outlets and the Chinese Financial Press. Support vector machine is applied to identify the positive, neutral and negative news within the articles. The study uses event study and logistic regression to examine the effects of peer news on focal firms’ investor behaviour.

The results show that both good and bad news about leaders cause peers’ stock prices to increase initially, but then reverse within one quarter. Further analysis reveals that when leaders’ shares receive positive news coverage, institutional investors tend to exert excessive abnormal buying pressure on peers’ shares, resulting in overreactions. Conversely, retail investors do not actively trade on peers on leaders’ news day due to limited attention. In addition, the study shows that short-selling constraint inhibits bad news from reflecting in the stock prices.

The study highlights differences in investor behaviour. The finding that institutional investors tend to overreact more to peer firms’ news when focal firms are smaller and have a lower frequency of information disclosure supports the salient theory. This is consistent with the previous framework that suggests overreaction is more pronounced when it is difficult to combine external sources of information to evaluate the focal firms. In contrast, retail investors do not engage in active trading on peers on leaders’ news day due to the limited attention theory.

Generation Z makes up 20% of China’s population, and accounts for the highest share of household spend at 13% (vs. 3% for the United Kingdom and 4% for the United States). To advance marketers’ understanding about this group of consumers and capitalise on China’s booming market, this chapter uses rich statistics and information to show that China’s Generation Z has distinct behaviour patterns, which can be attributed to the unique background in which they grew up: (1) rigidity of social stratification, (2) abundance of materialism, (3) digital era, (4) limited (vs. extended) family, and (5) heavy schoolwork. Growing up in such a background, Generation Z’s lifestyle and consumption-related attitudes and behaviour are distinct from their predecessors. The chapter presents specific actions that marketers can take when targeting this distinct group of consumers in China, along with useful guidelines to HR managers for hiring them.

More and more foreign companies, including multinational companies, open business in China. The staff management under the local culture of China is one of the critical points affecting the success of foreign invested companies in China. This paper aims to illustrate the effective methods of staff management for foreign invested companies in China.

For this purpose, a survey on concrete practices of staff management was conducted among three multinational company affiliates in China, whose parent companies are located in the USA, Japan, and Europe, respectively, by the in‐depth interviews with the high‐level executives of the affiliates.

It was found that although the staff management experiences of the surveyed affiliates show differences in operation, the affiliates have a common sense on how to balance culture difference, how to effectively communicate with staff, and how to appraise the performance. The active and passive factors of these experiences were further analysed from the needs level under current Chinese economic situation and from the invisible impacts on human behaviour of Chinese culture.

This study surveyed only three multinational company affiliates in China and therefore, the understanding obtained is limited in scope. The comprehensive knowledge of the subject depends on more case studies.

The analysis reveals that the active factors and localization, especially localization of the management team, are very important to the staff management of foreign invested companies in China.

The paper contributes to the research on effective methods for staff management in multinational companies.

This study aims to develop a bimodal nano-silver paste with improved mechanical property and reliability. Silicon carbide (SiC) particles coated with Ag were introduced in nano-silver paste to improve bonding strength between SiC and Ag particles and enhance high-temperature stability of bimodal nano-silver paste. The effect of sintering parameters such as sintering temperature, sintering time and the proportion of SiC particles on mechanical property and reliability of sintered bimodal nano-silver structure were investigated.

Sandwich structures consist of dummy chips and copper substrates with nickel and silver coating bonded by nano-silver paste were designed for shear testing. Shear strength testing was conducted to study the influence of SiC particles proportions on the mechanical property of sintered nano-silver joints. The reliability of the bimodal nano-silver paste was evaluated experimentally by means of shear test for samples subjected to thermal aging test at 150°C and humidity and temperature testing at 85°C and 85 per cent RH, respectively.

Shear strength was enhanced obviously with the increase of sintering temperature and sintering time. The maximum shear strength was achieved for nano-silver paste sintered at 260°C for 10 min. There was a negative correlation between the proportion of SiC particles and shear strength. After thermal aging testing and humidity and temperature testing for 240 h, the shear strength decreased a little. High-temperature stability and high-hydrothermal stability were improved by the addition of SiC particles.

Submicron-scale SiC particles coated with Ag were used as alternative materials to replace part of nano-silver particles to prepare bimodal nano-silver paste due to its high thermal conductivity and excellent mechanical property.

Although the use of project teams is on the rise, there is a limited understanding of how project managers can ensure project team success. Research to date is relatively broad and does not pinpoint how and why leadership influences success in a project team context. Along these lines, we draw from social learning theory to illustrate that ethical leadership influences project success through leader trust and knowledge sharing.

We collected data from 175 project team members from the information technology and software industry to evaluate our hypotheses. The results were analyzed using structural equation modeling.

Our findings support our hypotheses, illustrating that ethical leadership is related to leader trust and knowledge sharing, and that leader trust and knowledge sharing mediate the relationship between ethical leadership and project success.

Our work illustrates that the behaviors inherent in ethical leadership may be particularly well-suited for these project team challenges. Ethical leaders help team members understand that project success is possible when team members are transparent with one another, discussing their goals and challenges, and then working together to ensure their actions are coordinated in a way that increases the success of the overall project.

For those in industries or organizations where project teams are commonly used, our study may help to attract, select, and retain project managers that exhibit ethical leadership tendencies. Project managers are likely to be attracted to settings that align with their leadership style. Thus, organizations could focus on developing a culture that focuses on process over results.

We sought to align with the contingency approach to leadership, which suggests that the ideal leadership style depends on the followers, and the context in which the leader and followers interact. Specifically, we investigate ethical leadership as an ideal approach for project managers influencing members of their project teams. Our study demonstrates how ethical leadership is an ideal, context-specific approach that project managers can apply to increase the chances of project success.

A novel semiconducting macromolecule-polyperylene tetraamide (PPTI) was first synthesized with a simple method using 3, 4, 9, 10-perylene tetracarboxylic acid (PTCA) and hydrazine hydrate (N2H4).

The Ag nanoparticle was doped on the surface or inside of the PPTI film to obtain a highly sensitive hydrazine sensor-Ag/PPTI, which was synthesized within one step. The structure of Ag/PPTI was characterized through various techniques such as Fourier transform infrared (FT-IR), thermogravimetric analyzer (TGA), X-ray diffraction (XRD), X-ray photoelectron spectroscopy measurements (XPS) and scanning electronic microscopy (SEM).

According to cyclic voltammetry results, Ag/PPTI/GCE indicated good electrocatalytic activity toward the oxidation of hydrazine. The amperometric detection of hydrazine was then applied on Ag/PPTI/GCE. It exhibited a wide linear range from 0.05 to 50 µM, a low detection limit (S/N = 3) of 0.05 µM and high sensitivity of 0.45 µA/(µM•cm2).

In authors’ perception, this approach emerges as an effective technique for developing efficient chemical sensors for environmental pollutants.

The objective of this study is to examine the various factors that exert an influence on the green economy. This study also investigates the impact of foreign direct investment (FDI) on the Malaysian economy, specifically focusing on its position as a mediator. This research also examines the correlation between FDI and its influence on the contemporary green economy.

The authors employed quantitative methodologies and a self-administered survey to evaluate data and derive a definitive conclusion. The result was constructed using SPSS and SEM-PLS as the analytical software.

The study reveals that technological advancement, investment country and government policy significantly and positively affect the green economy, catalyse SDG goals and restructure the economy in better shape.

The current empirical research bridges the research gap in the context of technology advancement in government policy from emerging economies by exploring important factors, proposing their impact on the performance of the green economy, and empirically testing those hypothesized relationships. This study deciphers that FDI influences the green economy, where the investment country plays a significant role. Also, for a graphical presentation of this abstract, see the online appendix.

Environmental pollution and corresponding adverse health impacts have now become a significant concern for the entire planet. In this regard, analysts and experts are continually formulating policies to reduce environmental pollution and improve natural ecological conditions. To aid in coping with the ecological predicament, a framework has been developed in the present study to inspect the adverse environmental impacts and related health issues of coal mining.

The parameters for this study have been identified through a review of the literature and finalized 23 critical parameters of air, water, land and soil, and noise related to coal mining by consultation with experts from industry and academia. Finally, the parameters have been categorized in accordance with the level of threat they pose to the environment by assigning weight using the Bradley–Terry model considering attitudinal data acquired by a questionnaire survey.

It is found that coal mining has a relatively higher impact on four attributes of “air pollution” (suspended particulate matter [SPM], respiratory particulate matter [RPM], sulfur dioxide [SO₂] and oxides of nitrogen [NO_x]), followed by “land and soil pollution” (deforestation and surface structure diversion), “noise pollution” (vehicle movement) and “water pollution” (water hardness, total solids (TSS/TDS) and iron content). It is also found that raising the air concentration of SPM and RPM results in increased respiratory and cardiopulmonary mortality. Therefore, reducing dust concentrations into the air generated during coal mining is recommended to reduce air pollution caused by coal mining, which will reduce contamination of water and land and soil.

The model built in this study is a hypothesized model that relied on the experts' opinions considering the parameters of coal production only. However, the parameters related to the usage of coal and its consequences have been excluded. Further, only industrial and academic experts were considered for this study; however, they excluded local people, coal mining personnel, policy authorities, etc. Therefore, the study findings might differ in real circumstances. The research can further be reproduced by considering the parameters related to the use of coal and its consequences, considering the opinions of the local people, coal mining personnel and policy authorities.

Categorizing the parameters according to the threat they pose to the environment due to coal mining can help the decision-maker develop an effective policy to reduce environmental pollution due to coal mining by considering the parameters on a priority basis. In addition, the results further help the decision-makers to assess the environmental impact of coal mining and take necessary action.

The study has developed a framework using the Bradley–Terry model to categorize the environmental parameters of coal mining to develop effective environmental policies, which are original and unique in nature.