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The widespread use of information and communication technologies enables consumers to obtain and share information whenever they feel the urge. With the advent of review websites and forums, companies and business owners may find themselves victims of consumer cyber aggression, which can hurt a company badly. This study aims to explore why consumers would engage in cyber aggression against companies, and to that end, it examines consumers’ ethical orientation and other possible drivers of cyber aggression.

To examine how ethical orientation affects consumers’ intention to engage in cyber aggression, a scenario-based 2 × 2 (deontological: moral/immoral × teleological: good result/bad result) between-subject experimental design is used. Moreover, 26 possible drivers in related literature are identified and included in a questionnaire administered to 226 college students.

The results show that adult consumers’ deontological and teleological evaluations significantly affect their ethical judgment about engaging in cyber aggression, which further impacts their intention to perpetrate an act of cyber aggression. Moreover, the study identifies six factors contributing to cyber aggression engagement as follows: personal aggressiveness, ease of perpetration, internet negativity, personal gains, helping the company and recreation.

Cyber aggression is generally viewed as interpersonal violence among adolescents. This study views cyber aggression from a different perspective and it is one of the few studies to look at adult consumers’ motivations to engage in cyber aggression against companies. The findings of this study can help firms understand why their customers attack them online, and understanding that will enable businesses to formulate more effective responses to attacks.

Purpose – This chapter aims to explore the strategies used by the Hong Kong government to respond to the adult worker model and the male-breadwinner model; and to explore the views of women on the desirability of these strategies. The male-breadwinner model posits that men work full-time outside the home and women take on domestic work. The adult worker model suggests that women and men should be equally expected to participate in formal employment.

Design/methodology/approach – This chapter analyses the policy measures used by the Hong Kong government to support women in their participation in formal employment and the local work-based pension scheme (the Mandatory Provident Fund) as well as other policy measures that offer potential for enabling family care providers to accumulate resources for secure retirement. Additionally, it draws on semi-structured interviews with 30 Hong Kong young women to examine their views on the extent to which the government supports them to save pension incomes.

Findings – This study shows that the Hong Kong government uses a ‘weak action strategy’ to respond to the adult worker model and the male-breadwinner model, and that this strategy fails to meet women’s diverse preferences for their roles in the labour market and the family.

Originality/value – Based on a newly developed framework, this study examines the responses made by the government to both the male-breadwinner model and the adult worker model. It sheds new insights into possible ways of assisting women to achieve secure retirement .

The Formula 1 World Championship Japanese Grand Prix (denoted SUZUKA F1) has been held in Suzuka city in the Mie Prefecture of Japan every year since 2009. This event gathers a large number of motor racing fans around the circuit. The total number of attendees over three days amounts to more than 200,000. Reducing the traffic congestion around expressway interchanges (ICs) and decreasing the departure times of return traffic during peak hours are of critical importance not only for short-term transportation demand management (TDM) measures but also for sustainable development ­management in Suzuka city as a tourism destination. The chapter starts a brief review of previous studies on the TDM measures to identify the current trends in both their methodological and problem-oriented approaches and then introduces our approach called the area marketing and management approach (AMMA) relating to an issue on how we can pursue the sustainable development in tourism destinations. Based on the concept of the AMMA, a set of the Smart TDM measures are proposed involving the development of the application software that will be used as an interactive communication tool. The validity of the repeated applications of the Smart TDM measures is empirically examined by assessing the most recent experiences at the SUZUKA F1 until 2017. The limitations to what the current Smart TDM measures can do are finally discussed to improve the smartness of these TDM measures to contribute to the sustainable area development.

To improve unsafe workplace of Chinese SMEs, this paper aims to use the multi-agent simulation experiment to reveal the relationship between employees’ safety voice and safety level of enterprises.

Through simulation of employees’ safety voice activities, enterprises’ production activities, enterprises’ safety activities, an experiment platform is built. The experiment introduces external variable of labor resource and sets four experimental situations considering whether labor resource is sufficient and whether employees’ value is significant.

The result shows that not all the employees’ safety voice can change small- and medium-sized enterprises’ safety level. When there is sufficient labor supply, employee safety voice cannot improve the safety level of enterprises; when there is short of labor and employee safety voice is strong, safety level can be effectively improved. When employees have the strikingly different value variance, safety voice of common employees cannot improve safety level of enterprises, but employee safety voice with high value can improve safety level.

This fully provides that under the circumstances of disappearing demographic dividend in China, improving employees’ safety awareness and reasonably using their safety voice can boost SMEs to enhance safety level.

Outlines the findings of a study into the secondary destination choices of tourists visiting the Philippines. Defines the tourist mega‐system. Looks at the framework and methodology used and attempts to link these with the holistic approach of Jafari regarding tourism structure and stages which the tourists go through.

This paper aims to find proper technological parameters of low-temperature joining technique by silver sintering to eventually use this technique for reliable electronic packaging.

Based on the literature and author’s own experience, the factors influencing the nanosized Ag particle sintering results were identified, and their significance was assessed.

It has been shown that some important technological parameters clearly influence the quality of the joints, and their choice is unambiguous, but the meaning of some parameters is dependent on other factors (interactions), and they should be selected experimentally.

The value of this research is that the importance of all technological factors was analyzed, which makes it easy to choose the technological procedures in the electronic packaging.

This paper aims to employ social cognitive theory (SCT) as a theoretical framework to investigate the influencing factors affecting the knowledge transfer effectiveness of construction workers in China. The mediating role of their knowledge transfer willingness is also assessed.

A questionnaire on knowledge transfer among Chinese construction workers is designed and subsequently analyzed by structural equation modeling (SEM), with a total sample of 288 construction workers.

The SEM results show that the knowledge self-efficiency, blood and geographic relationships, and trust relationship promote knowledge transfer willingness and positively influence the knowledge transfer effectiveness of construction workers. However, the effect of organizational culture on knowledge transfer willingness and effectiveness is nonsignificant.

The results are conducive to managers and governments formulating strategies to optimize the learning mechanism of construction workers and facilitate their obtaining of resources from the project, thus easing skill shortages and promoting the transformation of construction workers into industrial workers.

This paper innovatively proposes blood and geographic relationships as research variables, expanding their scope. Furthermore, SCT is applied to enable future research to better understand individual knowledge transfer behavior from both personal and environmental perspectives.

Indoor air quality monitoring is extremely important in urban, industrial areas. Considering the devastating effect of declining quality of air in major part of the countries like India and China, it is highly recommended to monitor the quality of air which can help people with respiratory diseases, children and elderly people to take necessary precautions and stay safe at their homes. The purpose of this study is to detect air quality and perform predictions which could be part of smart home automation with the use of newer technology.

This study proposes an Internet-of-Things (IoT)-based air quality measurement, warning and prediction system for ambient assisted living. The proposed ambient assisted living system consists of low-cost air quality sensors and ESP32 controller with new generation embedded system architecture. It can detect Indoor Air Quality parameters like CO, PM2.5, NO2, O3, NH3, temperature, pressure, humidity, etc. The low cost sensor data are calibrated using machine learning techniques for performance improvement. The system has a novel prediction model, multiheaded convolutional neural networks-gated recurrent unit which can detect next hour pollution concentration. The model uses a transfer learning (TL) approach for prediction when the system is new and less data available for prediction. Any neighboring site data can be used to transfer knowledge for early predictions for the new system. It can have a mobile-based application which can send warning notifications to users if the Indoor Air Quality parameters exceed the specified threshold values. This is all required to take necessary measures against bad air quality.

The IoT-based system has implemented the TL framework, and the results of this study showed that the system works efficiently with performance improvement of 55.42% in RMSE scores for prediction at new target system with insufficient data.

This study demonstrates the implementation of an IoT system which uses low-cost sensors and deep learning model for predicting pollution concentration. The system is tackling the issues of the low-cost sensors for better performance. The novel approach of pretrained models and TL work very well at the new system having data insufficiency issues. This study contributes significantly with the usage of low-cost sensors, open-source advanced technology and performance improvement in prediction ability at new systems. Experimental results and findings are disclosed in this study. This will help install multiple new cost-effective monitoring stations in smart city for pollution forecasting.