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This research studies the influence and mechanism of rearing cost and endowment insurance on family fertility desire from the micro perspective.

Through the construction of overlapping generations (OLG) model and on the basis of this research purpose, the research hypothesis proposed by the theoretical model is tested by using the data of China household tracking survey (CFPS).

(1) Endowment insurance has an inhibitory effect on family fertility desire. The marginal effects of participating in old-age insurance on total fertility desire and boy fertility desire are – 3.2% and – 3.6% respectively. (2) The cost of rearing has a significant negative impact on family fertility desire. (3) There is regional heterogeneity in the impact of endowment insurance and rearing cost on fertility desire. (4) There is no significant difference in the impact of endowment insurance on fertility desire between urban and rural areas.

This research tries to fill the gap existing in the international literature by analyzing the micro mechanism of the influence degree of upbringing cost on fertility desire by introducing the rearing cost and fertility rate into the OLG, providing a micro basis for relevant quantitative calculation.

This research aims to explore how consumers' local brand choices differ between air-polluted days and clean days, and why the difference occurs.

Two studies were conducted. Study 1 used the longitudinal consumption data of various yogurt brands and daily air quality indexes in 2014 and 2015. Study 2 conducted three rounds of surveys on a clean day, a general air-polluted day and a seriously air-polluted day.

The findings indicate that consumers show less tendency of attribution and compensatory consumption during air-polluted days, which in turn decrease their willingness to choose local brands.

Implications are provided for future research and marketing practice, especially for local companies that rely heavily on local consumers, and retailers in heavy air-polluted areas.

This paper is the first to illustrate the influence of air pollution on consumers' local brand choices, and it extends current understanding on air pollution and consumer choices by discovering psychological process underneath to explain the effect.

As measurement results of optical gas sensors are constantly affected by the pressure of a target gas, approaches must be taken to modify the results. The purpose of this paper is to compare the traditional measurement method with the new measurement system. At the same time, measurement results of the two systems under different pressures are presented for comparison of the detection performance.

A theoretical model of line shape function and its impact on the measured results is presented, which is based on direct absorption and wavelength modulation spectroscopy (WMS) for gas concentration detection under different pressures. Methods of linear fitting and result modification have been illustrated and compared. A new testing system with the result modification method used for water vapor concentration detection under different pressures between 1 and 7 atm is applied. With an additional pressure sensor placed in the gas cell and calibration performed, relationships between the amplitude of the second harmonic and concentration of the target gas under different pressures can be obtained.

Amplitude detection can be used for concentration detection regardless of the change in pressure for the method of direct absorption. Although, WMS with second harmonic detection is not enough. Two methods are presented and compared with WMS under different pressures. Moreover, the result modification method shows better performance as computation is significantly reduced.

The comparison between linear fitting and the result modification method with WMS under different pressures is firstly presented. At the same time, a new testing system with better performance for water vapor concentration detection under different pressures is presented as well.

This research is to examine the impact of online channels on food stockpile behavior.

In this study, we use bivariate probit models to empirically investigate the impact of online purchasing channels on Chinese urban consumer food hoarding behaviors with random survey samples.

Results show that fresh food e-commerce channels are more likely to be associated with panic stockpile behaviors due to higher likelihood of supply shortages than offline channels with government assistance in logistic management. In contrast, community group buy, another format of e-commerce, appears superior in satisfying the consumer needs and easing the panic buying perception.

It suggests that online channels may have diverse impacts on consumers' panic stockpiling behaviors during the extreme situations. Online channels need to develop efficient supply chains to be more resilient to extreme situations and the government shall recognize the increasing share of the online channels together with traditional offline channels when implementing supporting policies.

With ever increasing share of online channels, it is imperative in terms of policy implications to understand how would online channels affect hoarding behavior.

We are the first study in online shopping's impact on food stockpile during pandemics using a random sample. Although food stockpile behavior at times of emergency have been investigated in many literature, there are no empirical studies on the impact of online channels on stockpile behaviors under extreme situations. Unlike disasters that immediately impact every entity in supply chains covering producers, vendors, distribution centers and retailers, pandemics did not render supply chains affected immediately, but rather increase consumers' willingness to shop online to avoid virus. Thus, Covid-19 provides a natural experiment to investigate the online channels' impact on stockpile behavior.

The purpose of this paper is to find a solution for the unmanned aerial vehicle (UAV) rendezvous problem, which should be feasible, optimal and not time consuming. In the existing literatures, the UAV rendezvous problem is always presented as a matter of simultaneous arrival. They focus only on the time consistency. However, the arrival time of UAVs can vary according to the rendezvous position. The authors should determine the best rendezvous position with considering UAVs’ maneuver constraint, so that UAVs can construct a formation in a short time.

The authors present a decentralized method in which UAVs negotiate with each other for the best rendezvous positions by using Nash bargain. The authors analyzed the constraints of the rendezvous time and the UAV maneuver, and proposed an objective function that allows UAVs to get to their rendezvous positions as fast as possible. Bezier curve is adopted to generate smooth and feasible flight trajectories. During the rendezvous process, UAVs adjust their speed so that they can arrive at the rendezvous positions simultaneously.

The effectiveness of the proposed method is verified by simulation experiments. The proposed method can successfully and efficiently solve the UAV rendezvous problem.

As far as the authors know, it is the first time Nash bargain is used in the UAV rendezvous problem. The authors modified the Nash bargain method and make it distributed, so that it can be computed easily. The proposed method is much less consuming than ordinary Nash bargain method and ordinary swarm intelligence based methods. It also considers the UAV maneuver constraint, and can be applied online for its fast calculation speed. Simulations demonstrate the effectiveness of the proposed method.