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Crowding in service environments is a constant concern for many firms due to the negative consequences it has on consumers and companies alike. Yet, scant empirical research exists on firm-generated initiatives aimed at improving customer service experiences in crowded situations. The purpose of this paper is to investigate how information, a managerially actionable variable, influences social interactions (in the form of customer social withdrawal and citizenship behavior) and service experience.

Two experimental studies were conducted using an extended service context.

This research demonstrates that receiving information about crowds in advance results in heightened social withdrawal, which improves customer service experience. However, providing consumers with a platform to share crowding information increases customers’ citizenship behavior toward service employees and other customers, which, in turn, improves customer service experience.

For extended service encounters (e.g. air travel) where social interactions are inevitable, companies should encourage customers to share their real-time experiences with other customers in hopes of creating more positive social interactions (e.g. citizenship behavior) within the crowded environment.

Existing investigations of crowding stem from an overemphasis on the physical and atmospheric aspects of the environment by treating crowds as a “fixture” in the servicescape, rather than as “active participants” involved in the crowding environment. While the mere presence of crowds alone has negative effects, this research takes it a step further by examining interactions among and between customers and service employees within the crowded service environment.

Object detection models have gained considerable popularity as they aid in lot of applications, like monitoring, video surveillance, etc. Object detection through the video tracking faces lot of challenges, as most of the videos obtained as the real time stream are affected due to the environmental factors.

This research develops a system for crowd tracking and crowd behaviour recognition using hybrid tracking model. The input for the proposed crowd tracking system is high density crowd videos containing hundreds of people. The first step is to detect human through visual recognition algorithms. Here, a priori knowledge of location point is given as input to visual recognition algorithm. The visual recognition algorithm identifies the human through the constraints defined within Minimum Bounding Rectangle (MBR). Then, the spatial tracking model based tracks the path of the human object movement in the video frame, and the tracking is carried out by extraction of color histogram and texture features. Also, the temporal tracking model is applied based on NARX neural network model, which is effectively utilized to detect the location of moving objects. Once the path of the person is tracked, the behaviour of every human object is identified using the Optimal Support Vector Machine which is newly developed by combing SVM and optimization algorithm, namely MBSO. The proposed MBSO algorithm is developed through the integration of the existing techniques, like BSA and MBO.

The dataset for the object tracking is utilized from Tracking in high crowd density dataset. The proposed OSVM classifier has attained improved performance with the values of 0.95 for accuracy.

This paper presents a hybrid high density video tracking model, and the behaviour recognition model. The proposed hybrid tracking model tracks the path of the object in the video through the temporal tracking and spatial tracking. The features train the proposed OSVM classifier based on the weights selected by the proposed MBSO algorithm. The proposed MBSO algorithm can be regarded as the modified version of the BSO algorithm.

The purpose of this paper is to understand the effect of store messiness and human crowding on shoppers' competitive behaviours, in-store hoarding and in-store hiding, through the mediating effect of perceived scarcity and perceived competition.

2 (store messiness: messy × tidy) × 2 (human crowding: high × low) between-subject factorial experiment was conducted online to manipulate retail store atmospheric factors. A total of 154 responses were collected through Amazon MTurk. The hypotheses were analysed using ANOVA and PROCESS (Hayes, 2013) procedure.

Results suggest that store messiness and human crowding within a fast-fashion store lead to perception of scarcity and competition that further affects competitive behaviours. When consumers experience store messiness, they are likely to hide merchandise in store, thus making it inaccessible for other consumers. Further, when they experience human crowding in the store, they feel that the products will be gone immediately so they have a tendency to hoard them.

This study examined the effects of scarcity perception by studying the case of fast-fashion retailers; generalizability needs to be established across different contexts.

Retailers by manipulating human crowding and store messiness can create a perception of scarcity in their stores, thus enhancing sales. However, they should also pay attention to deviant behaviours such as in-store hoarding and in-store hiding as these behaviours may decrease the store sales.

This research contributed to the retailing literature by finding a significant relationship between human crowding, store messiness and competitive behaviours through perceived scarcity and competition.

Since tourism is viewed as being a fast-growing industry, researchers are keen to investigate the negative impacts brought by an increasing number of visitors. As one of the derived social impacts, crowding has been proven to have a negative effect on tourists’ visiting experience. Thus, this study aims to understand tourists’ perception of crowding and its subsequent effect on their loyalty. A theme park in China called China Dinosaur Land, located in Jiangsu Province, is selected as the research site and 296 valid questionnaires are collected from the visitors. The results illustrate that psychological states, such as perceived crowding, emotional response, and coping behavior are much more complex than the study initially proposes; therefore, the hypotheses of the study are amended according to the research results.

The ubiquity of digitally intermediated interactions is changing the ways in which social interaction creates the cognitive and institutional underpinnings of new markets. Logics that define markets used to be localized, but they now emerge from crowds that span – and persist – across time and space. This article builds a theory of how crowds emerge and evolve in a way that influences the emergence of shared logics and helps explain why some markets are viable while others are not. What is revealed is that a crowd has a hidden niche structure that determines the fate of a new market.

In line with the stimulus overload theory, this study seeks a comprehensive understanding of tourism crowding by examining residents’ perceived tourism crowding and their corresponding avoidance and approach reactions through sustainable tourism. In addition, the study aims to investigate whether residents’ proenvironmental behavior moderates’ tourism’s negative impacts on the local ecosystem, delving into its potential mitigating role.

Using purposive sampling, the authors engaged residents associated with government and nongovernment organizations, universities, colleges and schools, as well as individuals from the business sector encompassing hotels, restaurants and cafeterias, markets and dedicated social activists actively involved in community affairs.

The analysis, conducted on 920 questionnaires using structural equation modeling, demonstrates that tourism crowding exhibits a negative correlation with sustainable tourism and approach reactions but a positive correlation with avoidance reactions. Furthermore, the moderation analysis suggests that as residents’ proenvironmental behavior improves, the detrimental effect of tourism crowding on sustainable tourism diminishes.

The study presents numerous implications for policymakers and the tourism industry, emphasizing the need to comprehend residents’ perceptions of tourism crowding and sustainable tourism. It underscores the importance of engaging residents in the tourism process to achieve sustainability goals.

The novel theoretical contribution lies in applying the stimulus overload theory to examine tourism crowding and sustainable tourism, specifically from the residents’ perspectives.

本研究根据刺激超负荷理论, 通过考察旅游地居民在整个可持续旅游过程中对旅游拥挤的感知以及他们的相应回避和接近反应, 寻求对旅游拥挤的全面了解。此外, 本研究旨在调查旅游地居民的环保行为是否可以缓和旅游对当地生态系统造成的负面影响, 并深入探讨潜在缓解作用。

我们采用目的性抽样方法, 邀请了与政府和非政府组织、大学、学院和学校有关联的旅游地居民, 来自商业领域（包括HORECA“酒店、餐馆和自助餐厅”和市场）的个人, 以及积极参与社区事务的专职社会活动家。

本研究采用结构方程模型（SEM）对920份调查问卷进行分析, 结果表明旅游拥挤与可持续旅游和接近反应呈负相关, 而与回避反应呈正相关。此外, 缓和分析表明, 随着旅游地居民环保行为的改善, 旅游拥挤对可持续旅游的不利影响呈现减弱。

本研究为决策者和旅游业提供了许多启示, 强调需要了解旅游地居民对旅游拥挤和可持续旅游的感知, 亦强调了让旅游地居民参与旅游过程的重要性, 以确保实现可持续发展目标。

本研究贡献了新颖的理论, 应用刺激超负荷理论考察旅游拥挤和可持续旅游, 特别是从旅游地居民角度进行考察。

Este estudio busca una comprensión global de la masificación turística mediante el examen de la masificación turística percibida por los residentes y sus correspondientes reacciones de aproximación y evitación a través del turismo sostenible, en el marco de la teoría de la sobrecarga de estímulos. Además, el estudio investiga si el comportamiento proambiental de los residentes modera los impactos negativos del turismo en el ecosistema local, profundizando en su potencial papel mitigador.

Utilizando un muestreo intencional o por juicio, se recogieron datos de residentes vinculados a organizaciones gubernamentales y no gubernamentales, universidades, institutos y escuelas, así como a personas del sector empresarial que engloba hoteles, restaurantes y cafeterías, mercados y activistas sociales que participan activamente en asuntos comunitarios.

El análisis de 920 cuestionarios mediante un modelo de ecuaciones estructurales demuestra que la masificación turística presenta una correlación negativa con el turismo sostenible y las reacciones de aproximación, pero una correlación positiva con las reacciones de evitación. Además, el análisis de moderación sugiere que a medida que mejora el comportamiento proambiental de los residentes, disminuye el impacto negativo de la masificación turística sobre el turismo sostenible.

El estudio presenta numerosas implicaciones para los responsables políticos y la industria turística, destacando la necesidad de comprender las percepciones de los residentes sobre la masificación turística y el turismo sostenible. Se subraya la importancia de implicar a los residentes en el proceso turístico para alcanzar objetivos de sostenibilidad.

La novedosa aportación teórica radica en la aplicación de la teoría de la sobrecarga de estímulos para examinar la masificación turística y el turismo sostenible, específicamente desde la perspectiva de los residentes.

The purpose of this paper is to examine how crowding without violating personal space influences consumers’ channel selection and the underlying mechanism of this process. Crowded environment is ubiquitous and affects consumers’ behaviors. However, less attention has been paid to whether and how crowding influences consumers’ preference for purchasing channels.

There were three studies to test the validity of the theorized model, including two laboratory experiments and a field study. The variance analyses and mediation analyses were used to give more insights into the analytical process.

This study proposes that crowding makes consumers lose their perceived control, leading them to form certain compensatory behavior through the conversion between online and offline purchasing channels – the type of goods moderates the process of compensatory behavior.

The results of this study are helpful for retailers to design effective strategies to allocate resources into online or offline channels and to choose the appropriate types of product to promote.

Environmental clues have been widely studied in previous marketing research. Crowding, as a common environmental clue, has only been noticed in recent years. This study examines the impact of crowding on consumers’ channel preference. The results of three studies have confirmed that consumers have higher preference for offline shopping when they are in a crowded environment and found the intrinsic mechanism and the marginal scenario of this process.

Recognizing that crowding in a restaurant waiting area forms a first impression of service and sets service expectations, the purpose of this study is to investigate the impact of crowding in the effective control of the waiting environment. The study seeks to examine the impact of crowding on customers' emotions and approach‐avoidance responses and to examine the mediating role of emotion and the moderating role of desired privacy in the relationship between crowding and approach‐avoidance responses.

Using real‐scale, interactive virtual reality (VR) technology that allows high‐fidelity representations of real environments, the authors created a navigable, photo‐realistic three‐dimensional model of a restaurant waiting area. Through an experimental study which manipulated crowding levels in the VR restaurant, they surveyed the subjects' responses toward crowding conditions.

The study found significant effects of crowding on emotions including arousal and dominance, but not pleasure, and on approach‐avoidance responses. The impact of crowding on approach‐avoidance responses was more direct than indirect, without having emotion as a mediator. It was also found that the desire for privacy as a psychological trait moderated the relationship between crowding and affiliation.

The findings of this study offer restaurant managers insights toward the effective management of the pre‐process service environment during the waiting state that minimizes the negative consequences of waiting/crowding. This study provides three courses of management actions that can make unavoidable crowding in the restaurant waiting situation more enjoyable and comfortable.

By using VR simulation, this study adds a new approach for crowding studies. Theoretically, this study broadened the scope of crowding studies by adding a potential mediating variable, emotions, and a moderating variable, desired privacy, in examining the relationship between crowding and approach‐avoidance responses. Also, by focusing on a restaurant waiting area, the authors were able to explore the pre‐process service expectations.

The purpose of this paper is to investigate the factors influencing quick cash by crowd in agri-food crowdfunding campaigns; this paper utilizes prospect theory to analyze the value and weighting functions of the crowd's cash.

Using samples of crowdfunding campaigns launched in the Zhongchou (www.Zhongchou.cn) platform's agriculture and food category, this paper employs a multivariate linear regression model to investigate factors that motivate the crowd to make quick investment decisions.

The results demonstrate that lowering the investment threshold, improving publicity, and increasing the benefits of a campaign can increase the decision weight assigned to a campaign, thereby motivating the crowd to make quick investment decisions. Improving the product's reputation, enhancing campaign promotion, and diversifying the reward scheme can increase the crowd's expected value of the campaign – another motivation for a quicker cash decision.

This paper can help initiators, platforms and regulators better fulfil their roles in promoting the rapid, healthy development of crowdfunding in the agri-food industry, especially in the context of the Chinese launch of significant initiatives to develop crowdfunding aimed at rural e-commerce and poverty alleviation.

This paper extends the behavioral finance concept of prospect theory to agri-food crowdfunding campaigns and investigates factors that motivate the crowd to make quick investment decisions. Additionally, this paper demonstrates that the backers of crowdfunding are not perfectly rational and can be motivated to invest by increasing mean decision weight and expected value of a campaign.

The purpose of this paper is to analyze the crowd stampede risk mechanism from the perspective of systems thinking.

Causal loop diagram is drawn to outline the non-linear interactions among complex factors across the whole system and dissect the contributory factors of crowd stampede accident. To systematically construct the theoretical framework and find fundamental solutions, co-word analysis with Citespace is used to get the critical data. An agent-based simulation using Pathfinder is conducted to develop a spatial model for the Shanghai Stampede Accident that happened in 2014.

The causal loop diagram is formed to not only illustrate the symptomatic solutions with a quick fix but also dissect the fundamental solutions through an underlying systemic analysis. The simulation shows that crowd stampede experiences an interactive process of accumulation, trigger, delay, break and diffusion of risk factors within the crowd system. A linkage effect among the multidimensional characters of individuals and the system accelerates the stampede risk deterioration. There exists delay of the result of effect from the deep-level measure.

A top-down approach is offered to policymakers for crowd stampede risk protocol design and synergic emergency control that may reduce the risk of the stampede.

In this study, SDFT paradigm is proposed as the critical solution for the crowd stampede accident. In addition, a chain effect of energy and a linkage effect within the crowd system is illustrated for in-depth understanding of crowd stampede risk.