The Psychology of Shopping Addiction in Consumer Behaviour

This comprehensive article examines the phenomenon of consumer addiction,primarily focusing on shopping addiction and its dimensions,including brand addiction.It delves into the underlying causes,manifestations,and consequences of consumer addiction from both consumer and marketer perspectives,shedding light on the ethical and cultural considerations within today's society.Consumer addiction is characterized by recurrent,irresistible purchasing behaviors driven by negative emotions such as anxiety and impulsivity.It is recognized as a behavioral addiction closely intertwined with consumerism.The article emphasizes the imperative for ethical marketing practices to mitigate the exacerbation of addictive behaviors while acknowledging the impact of culture on consumer choices.The article also discusses the crucial role of research in understanding the implications of consumer addiction on the economy,and it suggests that marketers should focus on fostering positive brand addiction rather than exploiting consumerism.It underscores the influence of cultural factors on addictive consumption and calls for responsible marketing practices and governmental regulations.In conclusion,this article highlights the critical significance of consumer addiction in the field of marketing and its multifaceted implications for both consumers and businesses.It underscores the need for ethical marketing strategies,cultural awareness,and responsible brand management to address this complex phenomenon in contemporary society.

Factors Affecting Consumers’Internet Shopping Behavior During the COVID-19 Pandemic:Evidence from Bangladesh

The aim of the study was to investigate the factors affecting consumers’internet shopping behavior during the coronavirus disease(COVID-19)pandemic in Bangladesh.The study measured the influence of product factor,price factor,time saving factor,payment factor,security factor,administrative factor,and psychological factor on consumers’internet shopping behavior during the coronavirus disease(COVID-19)pandemic.The research collected data from May 10,2020 to June 10,2020 in personal interview by online survey method through a structured questionnaire with five-point Likert scales from 230 Bangladeshi online consumers.Non-probability sampling method was used.Data were analyzed using descriptive statistics analysis,reliability analysis,and multiple regression analysis.Results exhibited that all factors except price factor and security factor had a momentous and positive association with consumers’internet shopping behavior during the coronavirus disease(COVID-19)pandemic in Bangladesh.It has implications for e-marketing practicing firms regarding the real strategy of online shopping for Bangladeshi consumers during the coronavirus disease(COVID-19)pandemic in Bangladesh.

Research on Consumers' WeChat Shopping Behavior Based on TAM Model

In the era when online shopping economy and online economy increasingly dominate social consumption,WeChat shopping has increasingly become a way that everyone accepts and is willing to try.This study applied Technology Acceptance Model commonly used in the field of information technology and rational behavior theory to the field of consumer behavior,and used the perceived ease of use and perceived usefulness in the technology acceptance model to explain consumers'willingness to use WeChat shopping.At the same time,the moderating effect of consumer innovativeness was also studied.The empirical results show that the main effect of perceived ease of use and usefulness is significant,and the moderating effect of consumer innovativeness is not significant.Based on the research results,the study puts forward the corresponding countermeasures and suggestions.

Consumers' Travel Behavior to Shopping Centers

Based on the questionnaire data,this study analyzes the characteristics of Wuhu citizens' travel behavior in shopping centers.The following conclusions are drawn:(1)the frequency of trips to shopping centers has a great correlation with consumersJ economic level and social status;(2)the time spent to purchase goods is positively correlated with the level of goods;(3)multipurpose shopping becomes the mainstream;(4)traffic becomes the primary factor for consumers to consider;(5)the availability of supermarkets and cinemas at shopping centers affect consumers'choice of shopping centers.

Relationship Between Built Environment, Socio-economic Factors and Carbon Emissions from Shopping Trip in Shenyang City, China

Promoting active travel behavior and decreasing transport-related carbon dioxide （CO2） emissions have become a priority in many Chinese cities experiencing rapid urban sprawl and greater automobile dependence. However, there are few studies that holistically examine the physical and social factors associated with travel CO2 emissions. Using a survey of 1525 shoppers conducted in Shenyang, China, this study estimated shopping-related travel CO2 emissions and examined how the built environment and individual socioeconomic characteristics contribute to shopping travel behavior and associated C02 emissions. We found that, firstly, private car trips generate nearly eight times more carbon emissions than shopping trips using public transport, on average. Second, there was sig- nificant spatial autocorrelation with CO2 emissions per trip, and the highest carbon emissions were clustered in the inner suburbs and between the first and second circumferential roads. Third, shopping travel CO2 emissions per trip were negatively correlated with sev- eral built environment features including population density, the quantity of public transport stations, road density, and shop density. They were also found to be significantly related to the individual socio-eeonomic characteristics of car ownership, employment status, and education level using a multinomial logistic regression model. These empirical findings have important policy implications, assisting in the development of measures that contribute to the sustainability of urban transportation and meet carbon mitigation targets.

Online Shopping: What Factors Determine Consumers to Buy?

This study analyzed factors influencing consumers in the process of making a decision in online shopping. The findings could inspire suggestions for online marketers in developing either media or infrastructures accordingly. The variables in the study involved product information, price, service, transaction safety, environment, age, gender, educational background, and income rate as independent variables, while the process of purchasing decision served as a dependent variable. Primary data were gathered in 10 locations within Jabodetabek areas involving 270 respondents which were analyzed using multiple regression analysis. The study revealed that price, information product, and service as significant variables influencing consumers in online shopping. Service became the most important factor for marketers to be considered as it emerged as the most dominant variable influencing the process of making a decision in online shopping.

Online Shopping:Antecedents of Attitude,Intention and Use

Consumer behavior in electronic commerce has been the theme of hundreds of studies conducted by researchers of many nationalities in the past twenty years.The purpose of this study was to review and classify the concepts used in papers published between 2003 and 2014 to explain the consumer behavior in electronic commerce.A systematic search of the literature in nine databases was performed and 136 papers published in double-blind peer reviewed journals were selected.Reference models were prepared based on a classification of the concepts found.This article reports only the concepts that displayed statistical significance in the studies analyzed.Finally,we suggest new studies that can be conducted.

Dimensions of Consumer's Perceived Risk in Online Shopping

Perceived risk is an important concept in consumer behavior in online shopping. It impedes the adopting online shopping. A structure model with seven factors of consumer's perceived risk in online shopping is developed in this paper. The results have the descriptive power about Chinese consumers' perceived risk in Internet shopping and provide framework for managerial use in China's e-commerce market environment.

基于特征分箱和K-Means算法的用户行为分析方法

针对网购用户所产生的购物行为进行分析,首先通过数据处理构建客户关系管理模型(RFM模型),在此模型的基础上采用特征分箱法和K-Means聚类两种方法对用户进行细分,并对2种模型结果进行比较分析,讨论二者的差异性和具体的应用范围和意义.其中,基于特征分箱法的RFM模型将变量转化到相似的尺度上并将变量离散化,使得用户分类标签更加清晰,也可依据各类标签分类出不同类型的用户.K-Means算法通过轮廓系数评估聚类算法质量以至于选取最优K值.本文实验分析结果可为运营商提供更加可靠直观的数据,使得运营商可以根据不同用户的不同行为进行市场细分,进而进行精准营销和服务设置.

直播购物情境下用户贡献行为影响因素研究

直播购物如何促进用户作出贡献行为是直播购物发展的关键。基于SOR理论,构建直播购物情境下用户贡献行为影响模型。研究发现,信息质量、品牌形象、主播专业性与直播互动性对感知愉悦与感知信任有正向影响;感知愉悦与感知信任对消费者冲动性消费与营销信息分享有正向影响;刺激环节的变量均通过感知愉悦与感知信任对消费者冲动性消费与营销信息分享的贡献行为产生正向影响;信息质量、品牌形象不能直接对冲动性消费产生影响,且品牌形象直接对消费者的营销信息分享产生正向影响;主播专业性、直播互动性不能直接对营销信息分享产生影响,对消费者的冲动性消费产生负向影响。

探索消费者心理需求与导购策略设计研究

该研究旨在探索消费者购物心理与导购策略之间的关系,以有效吸引消费者参与购物过程。通过分析消费者行为模式和心理需求,提出了吸引消费者、提升购物体验和商品选择便利性的策略。以商业综合体内信息传递效率低、对顾客吸引不足等问题为设计切入点,旨在指导商业综合体智能导购交互界面的设计研究。此外,还探讨了智能化设计的规律和导购机器人的交互方式,以增加购物乐趣。

拉萨农牧民网络购物行为特征及民生影响研究

农村电商得到了国家政策上的高度重视和支持,成为改善民生和促进产业发展的重要抓手。网络购物作为农村电商的重要组成部分可以显著改善农牧民的购买现状,满足农牧民个性化、多样化的商品需求,降低生产生活成本、提升生活品质。文章利用拉萨农牧区民生发展调查(TLDR,2021)数据,对农牧民网络购物参与情况从县区、年龄、学历、收入等角度进行差异性分析,并对具体的农牧民网络消费行为特征归纳总结,探讨网络购物对农牧民民生的影响。提出在不断提升农牧民收入水平的前提下,为了平衡城乡数字鸿沟,应该继续大力推进西藏的“电子商务进农村工程”,不断完善农牧区电子商务服务体系,培养农牧民网上购物习惯,促进城乡消费模式一体化发展。

旅游产品直播购物情境下消费者购买行为的前因及其影响机制

直播购物已成为一种新的消费模式,但目前缺乏对直播间消费者购买旅游产品的行为研究。基于刺激-机体-反应范式,文章采取质性研究方法,探讨旅游产品直播购物情境下消费者购买行为的前因及其影响机制。研究发现:1)除信息质量和主播信息源特性外,旅游产品的独特性和直播购物平台的类型、可信度及营销力亦是影响消费者购买行为的外部刺激;2)消费者对外部刺激的内在感知包括观看旅游产品直播时的沉浸状态、感知易用性和感知有用性,影响其对旅游产品直播购物的态度、观看意愿和购买行为;3)消费者是否会从直播间的“观望者”转变成“购买者”,受旅游消费者自身特质及其感知风险的影响。通过厘清各前因变量之间的关系,及其对直播间消费者购买旅游产品行为的影响机制,文章深化了对消费者购买行为的理解,并为旅游产品直播购物行业长效发展提供了理论支撑。

UWB室内定位技术在室内菜市场空间中的应用与研究

城市中菜市场室内空间的优化提升,直接影响着周边居民的购物体验和决策过程,而针对菜市场中购物行为模式的探索可以为菜市场改造提供依据。本文通过运用UWB室内定位技术获取菜市场内的行为样本数据,并对数据进行可视化呈现与分析。实验结果表明,高精度的室内定位数据可以准确描述菜市场这类大空间内的行为规律与空间偏好,对促进购物行为模式探究与菜市场优化设计具有重要意义。

消费情绪对生鲜农产品消费者购买行为的影响--基于网络直播情境的研究

网络直播过程中情绪互动发挥着维系消费关系的纽带作用。为了更好地促进生鲜农产品网络直播达成购买,带动生鲜农产品产地直接销售,本文针对直播中消费者情绪因素的作用开展机制研究。首先从理论上剖析了情绪因素对生鲜农产品网络直播购买意愿向购买行为转化的影响机理,随后在量化分析中运用配对样本T检验证实了意愿与行为的不一致,并且利用分层回归和分组回归检验了情绪因素的调节效应。结果显示:愉悦情绪、消极情绪和信任情绪对消费者的购买意愿转化为购买行为具有显著调节作用。具体而言,直播间抢购氛围唤醒的愉悦情绪和官员直播情境下的消费者信任情绪能有效促进意愿向行为转化,而负面社交环境下的消极情绪则阻碍了消费行为达成。

基于信任转移视域的社群购物用户消费行为实证研究

[目的/意义]随着电子商务发展并下沉至虚拟社群,社群已成为电商企业满足用户精准化需求的重要营销方式。通过探究用户参与社群购物的影响机理,可为社群运营发展提供有价值的决策参考。[方法/过程]基于信任转移视角,构建从移动端购物转移至社群购物的用户消费行为实证模型。以TAM理论为基础,利用SPSS 27.0和AMOS 28.0工具对收集到的数据进行检验。[结果/结论]用户对移动端购物信任既直接影响其对社群购物的信任,又借助感知有用性和结构保证两个因素间接影响社群购物信任,主观规范、感知易用性、感知有用性、社群购物信任因素可正向影响用户消费行为。

基于直播情境的消费者跟随行为研究

数字化时代,直播电商已成为一种重要的在线营销方式,其互动特性和实时性使得消费者的购物体验获得全新升级。研究直播环境下消费者如何受到各种因素的影响而产生购买行为,对商家优化直播营销策略、提高销售效率具有实际指导价值。基于此,论述了直播情境的内容与互动方式,分析了直播情境中的影响因素和消费者跟随行为的动机,并提出了相关影响措施,旨在揭示直播环境中消费者行为的内在逻辑和外在表现。

直播情境下家具类商品消费者行为影响机制探析

短视频App在影响人们生活方式的同时,也在重塑着消费者在线购物行为。选择S-O-R消费者决策模型,通过对59名在抖音直播间购买家具类商品的典型消费者进行访谈资料收集,并结合专家焦点小组访谈,探究影响消费者行为产生的核心概念及作用机制。结果表明,直播吸引力及主播专业性是影响消费者购买行为的外部刺激因素;消费者接受外部信息刺激后产生的内在情感变化,包括观看家具类商品直播的直播沉浸感、消费获利感、产品价值感和交互愉悦感会进一步影响消费态度,最终引发消费行为。此外,信息质量、主播魅力具有触发上述外部刺激因素及内在情感变化的中介作用。对消费者行为影响机制的分析,可加深对消费者在直播情境下购买家具类商品行为的理解,为商家提高家具类产品直播购买效果提供参考。

基于眼动数据的用户在线购物时间压力识别研究

【目的/意义】旨在基于眼动数据建立机器学习模型以识别出用户购物时的时间压力水平。【方法/过程】共招募了32名被试进行了一项有关购物的眼动追踪实验,让被试在不同的时间压力水平下执行四项任务,选择随机森林、支持向量机、梯度提升树和k近邻等机器学习算法构建识别模型,利用准确率、查全率、查准率、F1值和ROC等指标评估模型。【结果/结论】随机森林有着最好的识别精度,在测试集上的预测准确率达到了87.5%,其中注视持续时间和注视次数等注视类眼动指标为识别模型贡献最大。

The stay coefficient: a novel quantification of the relationship between stay time and travel time for urban shopping behavior analysis

Shoppers typically want to spend an amount of time at a destination that is proportional to the travel time required to arrive there;thus,the travel time can be considered the cost of their trip.This is likely to be the case across regions with different urban structures and cultures.The purpose of this study was therefore to analyze the shopping behaviors contained in travel survey data from three metropolitan areas in Japan to identify common patterns and indicators based on travel time and stay time,thereby obtaining an understanding to inform future trade area analyses.Both the travel time and stay time associated with shopping behavior were found to be log-normally distributed regardless of metropolitan area,and four shopping behavior patterns common among the metropolitan areas were identified.The“stay coeffi-cient”was then defined to express the elasticity of stay time according to travel time,and its values were similar according to shopping behavior pattern regardless of metropolitan area.The stay coefficient proposed in this study can therefore be applied to identify shopping behavior patterns in any urban area based on the relationship between travel time and stay time,realizing a novel approach to the analysis of and marketing for trade areas when planning the construction or renovation of commercial facilities.This approach can help inform the decisions of urban policy makers,marketing advisors,and commercial facility operators,and should be of interest to researchers and practitioners working with geospatial,shopping,and other human behavioral characteristics.