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Consumer engagement has been designated as an approach to describing online interactions that more comprehensively reflects the nature of consumers’ interactive relationships in online brand communities. This paper aims to explore consumers’ brand community engagement in the context of Facebook brand pages. This research puts forth the hypothesis that consumers’ brand community engagement on Facebook is dependent upon two overarching themes: external social forces and internal personal forces.

Based on social impact theory, social identity theory and social exchange theory, a conceptual research model is developed and empirically tested through structural equation modelling using cross-sectional data of 460 Facebook brand fans.

The empirical results suggest that internal personal forces primarily positively influence brand community engagement, while external social forces can even impact consumers’ brand community engagement negatively.

Future research should test and validate the proposed model for specific categories and brands.

This paper offers help to online brand marketers to trigger meaningful engagement of consumers in a brand community on Facebook.

This paper examines the consumer engagement construct from a behavioural perspective in a defined social media context and highlights the peculiarities of online brand communities on Facebook that distinguish them from traditional brand communities. The research uses a strong theoretical foundation to develop a model that investigates the prevalent variables that influence consumers’ brand community engagement on Facebook.

The recent economic/environmental discourse on development issues has led to a new paradigm of development, called here the “eco‐economic development model”, but usually known as sustainable development (including both ecological and economic concerns), which has successfully substituted the traditional model of economic development in general acceptance. However, new models usually imply new rules and perhaps a new type of market, yet policy issues within the eco‐economic development paradigm are being addressed with theoretical constructs and a state of mind as if we were still in the old paradigm – perhaps because the nature and the internal structure of the new paradigm are not yet well known and understood, as nobody has apparently looked into this. It should be expected that the two paradigms are not equivalent to each other, and therefore, they should be addressed differently. This paper presents a qualitative approach, from a systematic point of view, which can be used to highlight how different the two paradigms are in terms of structure and policy implications. Then, this information is used to provide an answer to three questions: is the economic development market the same as the eco‐economic development market; if not, how many invisible hands are there in the eco‐economic development market; and what are the environmental, social, and economic policy implications of this situation?. Shows that new paradigms require a new line of thinking to market policy and planning.

The purpose of this paper is to analyze and access the extent that emotion contagion (EC) affects the passenger aggressive behavior, and then reveal key factors triggering the passenger mass violence event (MVE) under an irregular flight situation.

This paper presents the group behaviors simulation framework based on multi-agent. The EC model is put forward to explore the EC effect among passengers, integrating the influence of intervention measures, power difference and intimacy. Moreover, the authors propose the aggressive behavior decision-making model tailed to the passenger MVE by combining the improved social force model and adaptive neuro-fuzzy inference system.

The experiment results show that the method proposed in this paper can simulate the realistic evolution process of passenger MVE .The EC effect among passengers is the catalyst for the quick spreading of MVE. The intervention measures, such as providing food and endorsing service, can effectively prevent from the MVE situation deterioration.

The research of this paper has important practical significance for the evolution analysis of passenger MVE and provides the basis for airport safety management.

Metro stations have become a crucial aspect of urban rail transportation, integrating facilities, equipment and pedestrians. Impractical physical layout designs and pedestrian psychology impact the effectiveness of an evacuation during a metro fire. Prior research on emergency evacuation has overlooked the complexity of metro stations and failed to adequately consider the physical heterogeneity of stations and pedestrian psychology. Therefore, this study aims to develop a comprehensive evacuation optimization strategy for metro stations by applying the concept of design for safety (DFS) to an emergency evacuation. This approach offers novel insights into the management of complex systems in metro stations during emergencies.

Physical and social factors affecting evacuations are identified. Moreover, the social force model (SFM) is modified by combining the fire dynamics model (FDM) and considering pedestrians' impatience and panic psychology. Based on the Nanjing South Metro Station, a multiagent-based simulation (MABS) model is developed. Finally, based on DFS, optimization strategies for metro stations are suggested.

The most effective evacuation occurs when the width of the stairs is 3 meters and the transfer corridor is 14 meters. Additionally, a luggage disposal area should be set up. The exit strategy of the fewest evacuees is better than the nearest-exit strategy, and the staff in the metro station should guide pedestrians correctly.

Previous studies rarely consider metro stations as sociotechnical systems or apply DFS to proactively reduce evacuation risks. This study provides a new perspective on the evacuation framework of metro stations, which can guide the designers and managers of metro stations.

The purpose of this paper is to develop a first-principles model for the simulation of pedestrian flows and crowd dynamics capable of computing the movement of a million pedestrians in real-time in order to assess the potential safety hazards and operational performance at events where many individuals are gathered. Examples of such situations are sport and music events, cinemas and theatres, museums, conference centres, places of pilgrimage and worship, street demonstrations, emergency evacuation during natural disasters.

The model is based on a series of forces, such as: will forces (the desire to reach a place at a certain time), pedestrian collision avoidance forces, obstacle/wall avoidance forces; pedestrian contact forces, and obstacle/wall contact forces. In order to allow for general geometries a so-called background triangulation is used to carry all geographic information. At any given time the location of any given pedestrian is updated on this mesh. The model has been validated qualitatively and quantitavely on repeated occasions. The code has been ported to shared and distributed memory parallel machines.

The results obtained show that the stated aim of computing the movement of a million pedestrians in real-time has been achieved. This is an important milestone, as it enables faster-than-real-time simulations of large crowds (stadiums, airports, train and bus stations, concerts) as well as evacuation simulations for whole cities.

All models are wrong, but some are useful. The same applies to any modelling of pedestrians. Pedestrians are not machines, so stochastic runs will be required in the future in order to obtain statistically relevant ensembles.

This opens the way to link real-time data gathering of crowds (i.e. via cameras) with predictive calculations done faster than real-time, so that security personnel can be alerted to potential future problems during large-scale events.

This will allow much better predictions for large-scale events, improving security and comfort.

This is the first time such speeds have been achieved for a micro-modelling code for pedestrians.

The purpose of this paper is to study dynamic evolution of passenger emotional contagion among different flights emerging in mass flight delays, so as to quantitatively analyze emotional variation tendencies and influences of concerned factors and intervention measures.

An intervening variable of group emotion was introduced into emotional contagion model to simulate passenger emotional evolution among multi-flight groups. Besides, personalities, characters and social relationships were considered to represent individual differences in emotional changes. Based on personal contact relationships, emotional contagion model was proposed to evaluate cross-emotion transition processes among different groups under scenarios of information shortage. Eventually, evolutionary processes of passenger emotions were fused in an agent-based simulation based on social force correction model.

Simulation experiment results revealed that passenger emotions suffer from combined impacts of individual emotional changes and emotional interactions among adjacent flights through a comparison with actual survey. Besides, emotional interactions accelerate processes of emotion transitions, and have significant impacts on adjacent flights when different measures are taken. Moreover, taking intervention measures simultaneously seems more effective than implementing intervention successively.

The proposed method makes up for deficiency of ignoring effects of emotional interactions among adjacent flights. It contributes to providing control methods and strategies for relevant departments and improving the efficiency and ability of handling passenger collective events in mass flight delays.

The purpose of this paper is to provide the possible and better selection for pedestrian flow evacuation.

Simulation.

First, according to the model with self-decision agents, the paper figures out that the effect of evacuation guided by the random-walk mechanism exceeds that guided by the inertial mechanism, and specifically, the effect of evacuation could significantly improve if random-walk agents restraint the probability of random walk under 0.4. Besides, on neighborhood reference mechanism, individuals who take neighbors’ average direction as reference tend to achieve better effect of evacuation than that of following majority rule. Furthermore, this paper proposes that an optimal ratio of the proportion of clever individuals and system density exists for evacuation effect improvement. Finally, the evacuating effect with barrier locating in different space is also studied in our research.

The effect of evacuation could significantly improve if random-walk agents restraint the probability of random walk under 0.4. On neighborhood reference mechanism, individuals who take neighbors’ average direction as reference tend to achieve better effect of evacuation than that of following majority rule.

The rapid evacuation of personnel in emergency situations is of great significance to the safety of pedestrians. In order to further improve the evacuation efficiency in emergency situations, this paper proposes a pedestrian evacuation model based on improved cellular automata based on microscopic features.

First, the space is divided into finer grids, so that a single pedestrian occupies multiple grids to show the microscopic behavior between pedestrians. Second, to simulate the velocity of pedestrian movement under different personnel density, a dynamic grid velocity model is designed to establish a linear correspondence relationship with the density of people in the surrounding environment. Finally, the pedestrian dynamic exit selection mechanism is established to simulate the pedestrian dynamic exit selection process.

The proposed method is applied to single-exit space evacuation, multi-exit space evacuation, and space evacuation with obstacles, respectively. Average speed and personnel evacuation decisions are analyzed in specific applications. The method proposed in this paper can provide the optimal evacuation plan for pedestrians in multiple exit and obstacle environments.

In fire and emergency situations, the method proposed in this paper can provide a more effective evacuation strategy for pedestrians. The method proposed in this paper can quickly get pedestrians out of the dangerous area and provide a certain reference value for the stable development of society.

This paper proposes a cellular automata pedestrian evacuation method based on a fine grid velocity model. This method can more realistically simulate the microscopic behavior of pedestrians. The proposed model increases the speed of pedestrian movement, allowing pedestrians to dynamically adjust the speed according to the specific situation.