Purpose: The purpose of this paper is to investigate the mediating effect of online reviewers' affect (ORA) on the relationship between weather and online review ratings (ORR).Design/methodology/approach: The consumers' online review data were collected from the third-party restaurant website, and the weather data were obtained from the weather part of Chinese e-government website. SnowNLP was utilized to analyze sentiment and further extract ORA. Furthermore, the mediating effects of ORA on temperature and ORR, rain and ORR were explored separately using PROCESS 3 Macro Model 4, and the interaction effect of temperature and rain was tested through PROCESS 3 Macro Model 7.Findings: The findings of this work demonstrate that ORA mediates the relationship between temperature and ORR and the relationship between rain and ORR. Besides directly leading to higher ORR, a higher temperature can bring about higher ORR by elevating ORA. On the other hand, little rain and heavy rain have a direct negative influence on ORR, and they can also lead people into a bad mood state, thus leading to lower ORR. Furthermore, temperature moderates the effect of rain on ORA. When the temperature is higher, the differences of ORA are larger between different types of rain than that of lower temperature.Originality/value: This study appears to be the first to investigate the relationship among weather, ORA and ORR using online data. The results could help managers understand when consumers are more likely to provide negative eWOM under corresponding weather conditions and adopt appropriate strategies to improve ORR.

The rapid development of Energy Internet (EI) has prompted numbers of generators to participate, leading to a hybrid power system. Hence, how to plan the hybrid power system and allocate its profit becomes necessary. In this paper, the cooperative game theory is introduced to discuss this problem. We first design the basic structure of EI, and point out the object of this study—coal power plant-wind farm-photovoltaic power station-energy storage provider (CWPE) alliance. Subsequently, average allocation strategy (AAS), capacity-based allocation strategy (CAS) and Shapley value allocation strategy (SAS) are proposed, and then the modified disruption propensity (MDP) index is constructed to judge the advantages and disadvantages of the three schemes. Thirdly, taking a certain area of A Province as an example, the profits of CWPE under three strategies are calculated respectively. Finally, by analyzing individual rationality and collective rationality of cooperative game and the MDP index of the three profit allocation schemes, we find that SAS is the most stable.

With the rapid development of energy Internet (EI), energy storage (ES), which is the key technology of EI, has attracted widespread attention. EI is composed of multiple energy networks that provide energy support for each other, so it has a great demand for diverse energy storages (ESs). All of this may result in energy redundancy throughout the whole EI system. Hence, coordinating ESs among various energy networks is of great importance. First of all, we put forward the necessity and principles of energy storage coordination (ESC) in EI. Then, the ESC model is constructed with the aim of economic efficiency (EE) and energy utilization efficiency (EUE) respectively. Finally, a multi-agent particle swarm optimization (MAPSO) algorithm is proposed to solve this problem. The calculation results are compared with that of PSO, and results show that MAPSO has good convergence and computational accuracy. In addition, the simulation results prove that EE plays the most important role when coordinating various ESs in EI, and an ES configuration with the multi-objective optimization of EE and EUE is concluded at last.