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China’s domestic tourism has developed quickly in the past 20 years. This article briefly reviews the scale of expansion in domestic tourism in China and summarizes three important factors contributing to that great change. In search of development trends, the article examines the main products of domestic tourism and government policy changes that influence tourism development. The conclusion is that China’s domestic tourism has shifted to the 3H (high input, high risk and high output) pattern. Besides intermediate‐long‐haul sightseeing and business tourism, domestic tourists frequently take medium‐short‐distance sightseeing trips and short‐distance weekend vacations, which forms ReBAM (Recreational belt around metropolis), a new tourist spatial pattern.

Aiming to find out how to incorporate green building into the architectural curriculum, this study aims to explore the psychological path for cultivating architectural students’ awareness and motivation to learn the green design concepts and related technologies.

Based on a global review of relevant architectural courses in universities, a set of green building learning behaviors was proposed and a survey was conducted in architectural schools in South China to verify the “value-belief-norm” theory through the lens of green building learning behaviors. The psychological path that affects students’ green building learning behaviors was analyzed using structural equation modeling.

The results showed that biospheric and altruistic values could directly affect students’ motivation to learn green building, while personal norms served as the mediating condition for personal values and beliefs, and ultimately improved motivation.

The study suggests that the cultivation of environmental awareness and a sense of the ecological crisis should be developed through foundation courses, by establishing an ecological architecture curriculum, to more effectively guide students to learn and practice green building.

This study, for the first time, applied the “value-belief-norm” theory, which was developed to explain the psychological path for pro-environmental behaviors, to green building learning behaviors of architectural students.

To solve the path planning problem of the intelligent driving vehicular, this paper designs a hybrid path planning algorithm based on optimized reinforcement learning (RL) and improved particle swarm optimization (PSO).

First, the authors optimized the hyper-parameters of RL to make it converge quickly and learn more efficiently. Then the authors designed a pre-set operation for PSO to reduce the calculation of invalid particles. Finally, the authors proposed a correction variable that can be obtained from the cumulative reward of RL; this revises the fitness of the individual optimal particle and global optimal position of PSO to achieve an efficient path planning result. The authors also designed a selection parameter system to help to select the optimal path.

Simulation analysis and experimental test results proved that the proposed algorithm has advantages in terms of practicability and efficiency. This research also foreshadows the research prospects of RL in path planning, which is also the authors’ next research direction.

The authors designed a pre-set operation to reduce the participation of invalid particles in the calculation in PSO. And then, the authors designed a method to optimize hyper-parameters to improve learning efficiency of RL. And then they used RL trained PSO to plan path. The authors also proposed an optimal path evaluation system. This research also foreshadows the research prospects of RL in path planning, which is also the authors’ next research direction.

The purpose of this paper is to put forward a multi-period dynamic pricing strategy for perishable food considering consumers’ price fairness perception. The impacts of the multi-period retail price, food freshness and inventory shortage risk on consumers’ heterogeneous willingness to pay (WTP) and their strategic purchasing behaviours are studied.

The authors present a price optimization model for perishable food, and conduct a laboratory experiment to justify the theoretical model. The data collected are analysed by correlation analysis and nonparametric test.

The results obtained reveal, first, food freshness and inventory shortage risk have effect on consumers’ heterogeneous WTP. Second, different retail prices lead to consumers’ strategically purchasing behaviours. Finally, consumers’ intertemporal price fairness perception and the food retailer’s long-term utility maximization can be achieved by developing multi-period dynamic pricing strategy.

This study suggests the perishable food retailer to apply a step-by-step price markdown strategy. It aims at eliminating price unfairness perceptions caused by loss of freshness and high shortage risk of the perishable food in the subsequent selling periods within the shelf life. Some valuable managerial insights towards perishable pricing for food retailers are discussed.

This study serves as the first step to utilize a laboratory experiment to dig out consumers’ intertemporal WTP towards perishable food. It also presents a novel way for describing consumers’ intertemporal price fairness perception by equalizing consumers’ average utilities considering consumer surplus, food freshness and shortage risk at different selling periods. The line of research on dynamic pricing concerning consumers’ price fairness perception is quite new in academic research, and has arisen due to its importance for food retailers of maximizing their long-term revenues and also of constructing mutual benefit and lasting connections with the consumers.