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The purpose of this paper is to investigate coexistence of multiple distribution systems in property‐casualty (P/C) insurance industry in the USA.

Stochastic frontier analysis is used to measure cost and revenue efficiencies of P/C insurance companies utilizing different distribution systems.

Independent agent insurers are found to be cost inefficient compared to insurers with other distribution systems, but the independent agent insurers have better revenue efficiency compared to their long counterpart, the exclusive agent insurers. This study also documents that the direct writing system provides higher cost and revenue efficiencies than other distribution systems, although their efficiencies have been deteriorating during the same time period.

Future research could examine whether the findings change by measuring efficiencies with a non‐parametric method, i.e. data envelopment analysis.

A start‐up insurer should consider a direct writing system, which is most cost and revenue efficient.

This paper investigates efficiencies of insurers by four different distribution systems and tracks efficiency changes of insurers over 12‐year periods.

The deposition of particles onto a substrate during the cold spraying (CS) process relies on severe plastic deformation, so there are various micro-defects induced by insufficient deformation and severe crushing. To solve the problems, many post-treat techniques have been used to improving the quality by eliminating the micro-defects. This paper aims to help scholars and engineers in this field a better and systematic understand of CS technology by summarizing the post-treatment technologies that have been investigated recently years.

This review summarizes the types of micro-defects and introduces the effect of micro-defects on the properties of CS coating/additive manufactured, illustrates the post-treatment technologies and its effect on the microstructure and performances, and finally outlooks the future development trends of post-treatments for CS.

There are significant discoveries in post-treatment technology to change the performance of cold spray deposits. There are also many limitations for post-treatment methods, including improved performance and limitations of use. Thus, there is still a strong requirement for further improvement. Hybrid post-treatment may be a more ideal method, as it can eliminate more defects than a single method. The proposed ultrasonic impact treatment could be an alternative method, as it can densify and flatten the CS deposits.

It is the first time to reveal the influence factors on the performances of CS deposits from the perspective of microdefects, and proposed corresponding well targeted post-treatment methods, which is more instructive for improving the performances of CS deposits.

The development of e-grocery allows people to purchase food online and benefit from home delivery service. Nevertheless, a high rate of failed deliveries due to the customer’s absence causes significant loss of logistics efficiency, especially for perishable food. The purpose of this paper is to propose an innovative approach to use customer-related data to optimize e-grocery home delivery. The approach estimates the absence probability of a customer by mining electricity consumption data, in order to improve the success rate of delivery and optimize transportation.

The methodological approach consists of two stages: a data mining stage that estimates absence probabilities, and an optimization stage to optimize transportation.

Computational experiments reveal that the proposed approach could reduce the total travel distance by 3-20 percent, and theoretically increase the success rate of first-round delivery approximately by18-26 percent.

The proposed approach combines two attractive research streams on data mining and transportation planning to provide a solution for e-commerce logistics.

This study gives an insight to e-grocery retailers and carriers on how to use customer-related data to improve home delivery effectiveness and efficiency.

The proposed approach can be used to reduce environmental footprint generated by freight distribution in a city, and to improve customers’ experience on online shopping.

Being an experimental study, this work demonstrates the effectiveness of data-driven innovative solutions to e-grocery home delivery problem. The paper also provides a methodological approach to this line of research.

The purpose of this paper is to use the most popular deep learning algorithm to complete the vehicle detection in the urban area of MiniSAR image, and provide reliable means for ground monitoring.

An accurate detector called the rotation region-based convolution neural networks (CNN) with multilayer fusion and multidimensional attention (M2R-Net) is proposed in this paper. Specifically, M2R-Net adopts the multilayer feature fusion strategy to extract feature maps with more extensive information. Next, the authors implement the multidimensional attention network to highlight target areas. Furthermore, a novel balanced sampling strategy for hard and easy positive-negative samples and a global balanced loss function are applied to deal with spatial imbalance and objective imbalance. Finally, rotation anchors are used to predict and calibrate the minimum circumscribed rectangle of vehicles.

By analyzing many groups of experiments, the validity and universality of the proposed model are verified. More importantly, comparisons with SSD, LRTDet, RFCN, DFPN, CMF-RCNN, R3Det, SCRDet demonstrate that M2R-Net has state-of-the-art detection performance.

The progress in the field of MiniSAR application has been slow due to strong speckle noise, phase error, complex environments and a low signal-to-noise ratio. In addition, four kinds of imbalances, i.e. spatial imbalance, scale imbalance, class imbalance and objective imbalance, in object detection based on the CNN greatly inhibit the optimization of detection performance.

This research can not only enrich the means of daily traffic monitoring but also be used for enemy intelligence reconnaissance in wartime.

This study aims to investigate the intentions of individuals’ monetary charity during the COVID-19 crisis in Kuwait. The new conditions of COVID-19 enhanced both the theoretical as well as empirical importance of understanding how charities canalize monetary donations toward those in need.

An initial framework is developed based on the theory of planned behavior (TPB) to conceptualize how an individual’s intention of donating money to charitable organizations is realized in their behaviors. A cross-sectional study of 276 donors is conducted.

Explained variance gained is 0.73% suggesting that during the pandemic, donors are financially able to donate and prioritize easily accessible channels to transfer monetary charity. Donor attitudes towards charitable organizations were found to be insignificant regardless of the mismanagement reported.

This study importantly discusses public behavior toward charities during the pandemic and suggests policies for managing such charities during a pandemic for optimizing their effectiveness.

This paper used a contemporary context to measure behavioral intentions including attitude (attitude toward making a financial donation, attitude toward charitable organizations and the attitude toward helping others), perceived behavioral control, descriptive norms, moral norms, injunctive/prescriptive norms and past behavior and thus enhance the empirical base of the TPB.

This study aims to investigate the vibration effects on ball grid array lifetime.

Several finite element method simulations and experiments were performed.

An optimized circuit configuration was found.

The originality of paper is confirmed by authors.

The purpose of this paper is to address the overarching question, which was whether the incentives programmes formulated for the community have been found to be suitable to the aspirations and needs of the local residents.

This study has resulted from the authors’ experience through conducting a survey with the local residents in three locations, namely the Bukchon Hanok Village located at Seoul metropolitan city; the Hahoe Village, Angdong and the Yangdong Village, Gyeongju; both the latter are located towards the west of the Korean peninsula in the Gyeongbuk-do Province. This study has hopefully tried to analyse the residents’ perception of the effectiveness of the current incentives policy by using the Bennett’s programme evaluation method.

Results show that there was a divergent direction between the current incentives policy and the local aspirations between sites. In most cases, the cultural heritage conservation has been found to be a catalyst to fulfil a heritage tourism advantage rather than to cater to the local community needs.

The paper is the first insightful study of the historic villages which attempts to draw out the importance of the effectiveness of the incentives programme in guiding the conservation efforts for the local economic development.

Adopting sustainable practices is highly required in hotels. This study aims to assess consumer behaviour towards adopting sustainable practices in hotels. In addition, mediating role of consumer attitude (CAtt) is assessed between consumer awareness (CA) and willingness to pay.

An empirical study was carried out to analyse the integrative research model of CA, CAtt and willingness to pay premium price (WTPPP) for sustainable practices adoption in five-star hotels in emerging economies. Responses from 447 respondents were collected and analysed. Structural equation modelling was performed using SPSS 21.0.

The research outcomes indicate the partial mediation of CAtt between CA and WTPPP. Furthermore, consumer satisfaction has been found to have a moderating effect on the relationship between CAtt and willingness to pay a premium price.

The research results add to the literature by analysing prominent factors affecting willingness to pay premium for adopting sustainable practices in five-star hotels.

This paper aims to examine the environmental awareness, initiatives and performance in the Macau hotel industry.

A mixed research method was adopted involving quantitative surveys with 31 hotels in Macau and 11 face-to-face interviews with the hotel managers, facilities managers and engineers.

Response from surveys and interviews with 31 hoteliers show that hotels in Macau have a high level of environmental awareness. Most hoteliers actively introduce initiatives that contribute to cost savings. Initiatives including using energy conservation light bulbs, having an active system to detect/repair leaking facilities and installing water conserving fixtures are widely implemented, while programs involving using solar lawn light, recycling leftover food and reusing wastewater are not. Major barriers for going green include the lack of government regulations on environmental management (EM), financial constraints, the lack of employees to handle EM and the fear that environmental initiatives may negatively impact the guest’s experience, especially those VIP and hardcore gamblers and customers who expect enjoying the luxuries services in Macau hotels. Lower star hotels experience more difficulties in adopting green approaches.

This paper presents a single case study of Macau; therefore, the results in this research may have limited generalizability.

This paper is one of the very few attempts that investigate EM in Macau – a renowned world tourism and gambling destination, where the vast majority of hotels have their casino facilities. Results show that apart from the financial consideration and the lack of government enforcement to adopt green measures similar to hotels in other destinations, EM practices of Macau’s hotels are also constrained by its customer base and the acute shortage of human resources that is caused by the tourism boom.

Considering that listed companies are the main body of natural resource consumption and pollutant emission, this study aims to explore the stock price effect and source channels of green bond issuance of listed companies. This is extremely necessary to promote listed companies to actively fulfill their environmental responsibilities so as to achieve sustainable economic and social development.

In this paper, the companies that issued green bonds in Shanghai and Shenzhen stock markets in China from 2016 to 2018 are used as samples. First of all, the authors adopt the event study method and match the two models to prove that there is a stock price effect in green bond issuance. Then, the authors introduce the general regression model to analyze the sources of the stock price effect of green bond issuance in detail through three channels: “financing cost,” “investor attention” and “fundamental.”

In the above three channels, the “investor attention” channel can well explain the stock price effect of green bond issuance. Meanwhile, the authors also find that the stock price effect of the subsequent issuance of green bonds is more significant than that of the first time, non-financial companies are more pronounced than financial companies, public issuance are more obvious than private issuance, state-owned companies are more notable than non-state-owned companies, small-scale companies are more evident than large-scale companies and companies with high equity concentration are clearer than those with low equity concentration.

Taking China as the research object for the first time, this paper comprehensively employs the capital asset pricing model and Fama–French five-factor model to discuss the stock price effect of green bond issuance of listed companies. Secondly, this paper also studies whether the way of green bond issuance, the type and size of the company, as well as the degree of ownership concentration will have different effects on the stock prices of listed companies. The research results provide new ideas and methods for the stock price effect of green bond issuance.