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This paper sets out to identify key success criteria for e‐business and consider emergent models which integrate the most value‐adding characteristics in response to the requirements of both consumers and business organisations.

In assessing differing models of B2C/C2C, the paper uses an adapted evaluation framework which brings together key factors identified from the literature. A Likert scale exercise undertaken enables the authors to subsequently rank models.

Analysis of the results from the differing models identifies 14 primary success factors from which the paper develops a modified ontology of e‐business. This is attributed to the evolving role of internet communities and social networking; the impact of “mobbing” and demand aggregation on rate of growth; and the effects of the “long tail” in differentiating markets into high‐diversity short‐run products.

It is recognised that the scoring exercise is based on a limited range of exemplars for each e‐model, which are ranked by a relatively small panel of experts. The expertise of those participating may also have constrained the validity of the results. However, there is significant consistency between the responses from each, indicating that the results are not unrealistic.

The paper discusses e‐business from a differing view to existing literature, which considers emergent trends such as the effects of the “long tail” and “mobbing” in isolation, rather than focusing on a discussion of value chain factors per se. The authors develop a modified ontology of e‐business based on a practical analysis of e‐business exemplars rather than comparative studies based solely on literature reviews.

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.

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.

This study aims to examine the impact of migration growth on environmental outcomes and local governance and assess how well the existing local municipal governance has responded to the environmental impact of increased migration influx in Ontario, Canada using the annual data during 2012–2021.

This study used the grey relational analysis (GRA) to examine the correlation degree between migrant growth, environmental outcomes and local governance, used coupling coordination degree model (CCDM) to access to what extent the existing local governance systems have responded to the environmental impact of immigrant growth.

Results show that higher immigrant populations are associated with worse environmental outcomes and the need for more municipal environmental investment and service. The present local municipal environmental service in Ontario lags behind in response to the environmental impacts of increased migration. Good local governance practices and environmental services are required to improve the environmental adaptation capacity of host countries to migrant influx.

Climate change has been regarded as an important driver of internal and international human migration. The mass influxes of migrants will threaten cities’ environmental quality and put considerable pressure on municipal services. This study provides empirical evidence for Ontario’s municipal environmental governance and relevant authorities on how to deal with the environmental impact of increased migration and contributes to call the attention of other countries to the urban environmental pressure caused by migration influx due to the changing climate world wide.

In recent years, some peer-to-peer (P2P) service sharing platforms have improved their service quality by setting an entry quality threshold for service providers. Considering consumers' heterogeneous preferences for service quality and commission rate, it is worth studying how to select the commission rate contract for a P2P platform under a predetermined entry quality threshold for service providers.

In this study, the platform's profit-maximizing model is constructed under two proposed contracts: unilateral commission rate contract and bilateral commission rate contract. The optimal entry quality threshold and the optimal commission rate are obtained. This study also explores the impacts of cross-side network externality and service price on a platform's optimal decisions and social welfare.

Results show that it is always advantageous for the platform to adopt the bilateral commission rate contract, which is closely related to the strength of cross-side network externality, service price and quality sensitivity coefficient. Under certain conditions, adopting the unilateral commission rate contract can reduce platform profit and service provider surplus, and improve consumer surplus and social welfare.

This study analyzes the unilateral commission rate contract and the bilateral commission rate contract of the platform, and discusses which contract is beneficial to the platform, consumers and service providers. In addition, this study provides a basis for the operation decision of a P2P service sharing platform and the pricing decision of service providers.

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.

The purpose of this paper is to design a disturbance observer-based finite-time global sliding mode control scheme for the attitude tracking control problem of the reentry vehicle with parameter uncertainties and disturbances.

Feedback linearization is first introduced to transform vehicle model into three independent second order uncertain subsystems. Then a finite-time controller (FTC) is proposed for the nominal system on the basis of the homogeneity theory. Thereafter the integral sliding mode method is introduced for the vehicle with disturbances. The finite time convergence is achieved and global robustness is also assured by the combination of finite time control method and integral sliding mode strategy. Furthermore, to improve the attitude angle tracking accuracy a novel finite time disturbance observer (DO) is constructed.

Simulation is made for the reentry vehicle with disturbances involved. And the results show the finite-time convergence, tracking accuracy and robustness of the proposed strategy.

The proposed control strategy has three advantages. First of all it can achieve finite time convergence and avoid singularity. Moreover, it can also realize global robustness. Finally, a new kind of DO is introduced to improve the tracking accuracy.

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.