Predicting Purchasing Behavior on E-Commerce Platforms: A Regression Model Approach for Understanding User Features that Lead to Purchasing

This research introduces a novel approach to improve and optimize the predictive capacity of consumer purchase behaviors on e-commerce platforms. This study presented an introduction to the fundamental concepts of the logistic regression algorithm. In addition, it analyzed user data obtained from an e-commerce platform. The original data were preprocessed, and a consumer purchase prediction model was developed for the e-commerce platform using the logistic regression method. The comparison study used the classic random forest approach, further enhanced by including the K-fold cross-validation method. Evaluation of the accuracy of the model’s classification was conducted using performance indicators that included the accuracy rate, the precision rate, the recall rate, and the F1 score. A visual examination determined the significance of the findings. The findings suggest that employing the logistic regression algorithm to forecast customer purchase behaviors on e-commerce platforms can improve the efficacy of the approach and yield more accurate predictions. This study serves as a valuable resource for improving the precision of forecasting customers’ purchase behaviors on e-commerce platforms. It has significant practical implications for optimizing the operational efficiency of e-commerce platforms.

Prediction of users online purchase behavior based on selective ensemble learning

A probabilistic multi-dimensional selective ensemble learning method and its application in the prediction of users' online purchase behavior are studied in this work.Firstly, the classifier is integrated based on the dimension of predicted probability, and the pruning algorithm based on greedy forward search is obtained by combining the two indicators of accuracy and complementarity.Then the pruning algorithm is integrated into the Stacking ensemble method to establish a user online shopping behavior prediction model based on the probabilistic multi-dimensional selective ensemble method.Finally, the research method is compared with the prediction results of individual learners in ensemble learning and the Stacking ensemble method without pruning.The experimental results show that the proposed method can reduce the scale of integration, improve the prediction accuracy of the model, and predict the user's online purchase behavior.

Consumer Purchase Behavior based on product concept learning

Form consumer learning perspective, a theoretical analysis of the structure of brand knowledge is gave. Product concepts will be transformed into knowledge nodes, association links and affective response which are stored in consumer memory. Consumer brand knowledge is composed of brand awareness, brand image and brand attitude. Data are collected from questionnaire. The structure of brand knowledge is confirmed by exploratory factor analysis. Form a binary logistic regression analysis of brand knowledge and consumer purchase behavior, it found that brand attitude is the main factor to predict and explain the purchase behavior based on product concepts.

Passenger Choice Behavior between Direct and Transit Flights——A Case Study on Passengers Using Hub Airports in the Northeast Asian Region

This study analyzes air passenger route choice behavior for long-haul inter-continental travel. It employs the SP （state preference） technique and logit modeling to investigate the impact of route development via neighboring countries in the region. With the Japanese government pursuing an increase in international routes at Haneda International Airport, and the Chinese government planning to construct Beijing Capital Second International Airport by 2019, the competition among airports to serve as hubs in Northeast Asia will increase significantly. Korean passengers will have a greater number of route choices when traveling to North America or Europe, utilizing not only direct flights from Incheon International Airport but also flights via Tokyo or Beijing area airports including Haneda International Airport, Narita International Airport, Beijing Capital International Airport and Beijing Capital Second International Airport. Accordingly, passengers will choose among the alternatives by considering fares and flight times. As such, it is essential for airports to offer flights with competitive prices for transit passengers to become successful competitive airports in the region. Therefore, it will become more important for market decision makers to strive toward more attractive ticket prices and better route network quality.

A Study on the Influence of External Stimuli and Psychological Processes on Stationery Purchase Behavior Based on SOR

Based on the SOR(stimulus-organism-response)model to obtain 534 survey data from the MTurk platform,the relationship between external stimuli,psychological processes,and consumers’stationery purchasing behavior was empirically analyzed using a multivariate ordered logistic regression model.In terms of marketing stimuli,consumers’recognition of product quality and price as well as the convenience of purchasing channels significantly and positively influenced purchasing behavior;in terms of social stimuli,self’s opinion of needs and the positive evaluation of peers significantly and positively influenced purchasing behavior;in terms of psychological process,consumers’knowledge,trust,willingness to know,and preference for stationery products significantly and positively influenced purchasing behavior.Accordingly,it is proposed that,in order to promote the purchase of stationery products,the production and operation links should ensure the quality of stationery products,promote price control in a reasonable range,guarantee a healthy,orderly,and convenient stationery market environment,as well as strengthen the multi-sensory promotion of stationery products.

Motives Underlying Organic Food Consumption in Turkey： Impact of Health, Environment, and Consumer Values on Purchase Intentions

Raising ecological awareness and health concerns create question marks about healthiness and sustainability of conventional foods in customers＇ minds. Due to augmented mass media coverage of environmental problems, health concerns related to consumption of genetically modified food and/or chemical contaminants in food, and consumers＇ increasing interest in healthy nutrition and environmental protection, there is a growing interest for organic foods in all over the world. Growing interest for organic foods, and increasing production and demand in organic food market has made organic food consumption a significant topic of research. Although organic food market and demand for organic foods have also been growing in Turkey, literature regarding organic food consumption is not very extensive. Therefore, this study aims to understand the underlying motives for organic food consumption in Turkey, and to explore the factors affecting Turkish consumers＇ attitudes towards organic foods and the behavioral intention of Turkish consumers to purchase organic food by the help of the theory of reasoned action （TRA）. The results of 622 successful surveys used for this empirical research indicate that Turkish consumers＇ attitudes towards organic foods are determined by perception of organic foods, consumer values, and price perception, while their purchase intention is determined by health consciousness, perception of organic foods, consumer values, price perception, and environmental concerns.

STUDY ON DYNAMIC CURVING BEHAVIOR OF TILTING PASSENGER CARS

By using tilting carbodies, train can negotiate at a higher speed withoutreducing the passenger's ride quality. This is a good method to allow a significant increase inspeed at existing track to improve the railway transportation capability, and to enhance thecompetition ability of railways with other transportation systems. With the increase of the curvenegotiation speed, the wheel-rail lateral forces and wheel-rail wear of the tilting train willincrease. The self-steering radial bogie is an effective way to solve the problem. The dynamic modelof the tilting passenger car with self-steering bogies is established in detail, and the curvingperformance of the car is investigated.

Consumer’s Purchase Intention towards Luxury Retailer’s Social Media Advertisements —A Case Study of a Shoe Retail—UAE-Dubai Mall

Digital marketing is considered the preferred method comparing to traditional marketing nowadays [1], but is it true for luxury and expensive products? Since the perception prevails that the concepts “luxury” and “digital” are quite incompatible [2], this paper aims to explore the effectiveness of digital marketing advertisements of luxury retailers, while also exploring consumer’s purchasing intent based on the viewing of such promotions. The overall goal is to provide a model of luxury purchase behaviour through harnessing social media. As a constructionist ontology-based researcher, I believe in multiple versions of reality which can evolve based on my target consumer experiences [3]. My epistemological stance is interpretivism with a subjective approach, inductively interacting with consumers to better understand what this “truth” means to them, incorporating textual material to support the analytical interpretations [4]. It is hoped this paper will inform fashion brands marketers about social media practice to achieve creation of purchase intention and ultimately achieve target sales. The paper is useful to both practitioners and academics in the fields of social media marketing and purchase intention. The research provides some initial insights into consumer perspectives of social media ads and online purchase behaviour.

Inter-Purchase Time Prediction Based on Deep Learning

Inter-purchase time is a critical factor for predicting customer churn.Improving the prediction accuracy can exploit consumer’s preference and allow businesses to learn about product or pricing plan weak points,operation issues,as well as customer expectations to proactively reduce reasons for churn.Although remarkable progress has been made,classic statistical models are difficult to capture behavioral characteristics in transaction data because transaction data are dependent and short-,medium-,and long-term data are likely to interfere with each other sequentially.Different from literature,this study proposed a hybrid inter-purchase time prediction model for customers of on-line retailers.Moreover,the analysis of differences in the purchase behavior of customers has been particularly highlighted.The integrated self-organizing map and Recurrent Neural Network technique is proposed to not only address the problem of purchase behavior but also improve the prediction accuracy of inter-purchase time.The permutation importance method was used to identify crucial variables in the prediction model and to interpret customer purchase behavior.The performance of the proposed method is evaluated by comparing the prediction with the results of three competing approaches on the transaction data provided by a leading e-retailer in Taiwan.This study provides a valuable reference for marketing professionals to better understand and develop strategies to attract customers to shorten their inter-purchase times.

Passenger Perceptions and Choice Behavior of National,Low Cost and Foreign Carriers:A Case Study on Incheon International Airport

Recently,the LCCs(low cost carriers)using ICN(Incheon International Airport)as a hub have increased their international routes.In addition,foreign nationality airlines,including Middle Eastern carriers,have gradually increased their operations at ICN.This growth in carrier services has resulted in a more competitive market environment,and reasonable resource assignment has become an important issue for airport operators.Moreover,the airport will open a new terminal—T2(terminal 2)in early 2018,and carriers will need to adjust their operations reflecting the utilization of newly assigned facilities.Motivated by this change,we investigate the differentiation of airport service perception as well as airline choice behavior by passenger groups at ICN.This paper employs a MNL(multinomial logit)model as well as a SEM(structural equation model).The results indicate that airline gate allocation is a significantly important value for passengers in terms of airport service perception and choice behavior.Passenger perception and choice behavior differ according to the selected carrier.This study concludes that it is significantly important to consider the characteristics of passenger perception and choice behavior to improve airport operational efficiency,particularly with respect to carrier facility assignment.

The Relationship between Consumers'Public Self-consciousness and their Purchase Intention of the New Luxury Goods

The era of consumption upgrade has begun due to the rapid economic development.Nowadays,the new luxuryconsumption is prevailing,and China has emerged as the primary consumer of these luxury goods.Based on the public self-consciousness of consumers,the relationship between this aspect and consumers'purchase intentions of the new luxury goodsis explored.This study investigated the impact of consumers'public self-consciousness on their willingness to purchase newluxury goods,validated the proposed hypothesis by design experiments,and used the linear regression analysis of theexperimental data.This study showed that the higher the consumer's public self-consciousness,the more inclined they wereto purchase these luxury goods.The findings of this study would be helpful to expand and enrich the researeh of the newluxury consumption behaviors in consideration that public self-consciousness is hardly reflected in recent research.Hence,this study would enlighten and acts as a significant reference for companies of the new luxury goods to develop more effectivemarketing strategies.

公众森林碳汇购买意愿影响因素研究——基于TPB—NAM整合模型

有效的碳普惠机制与森林碳汇产品的价值实现对中国生态文明的建设至关重要,理清公众森林碳汇购买意愿影响因素对森林碳汇政策的制定具有现实意义。基于计划行为理论、规范激活理论并融合生态文明思想内核,选用结构方程模型,利用515份社会公众问卷数据,实证检验了公众森林碳汇购买愿意影响因素及作用机理。结果表明:(1)公众森林碳汇购买意愿是理性和道德交互作用的结果,而非纯理性或纯道德驱动行为;(2)行为态度、感知规范和知觉行为控制都对公众森林碳汇购买意愿具有显著正向影响,但影响程度具有差异性,其中感知规范对购买意愿影响最大,因此公众环境道德素养是影响其森林碳汇购买行为的最重要因素;(3)社会公众森林碳汇购买意愿影响因素表征变量的具体作用表现不同:感知规范中,公众个体道德规范对其森林碳汇购买意愿影响最大;行为态度中,公众森林碳汇生态、政治效益认知对购买意愿影响最大;知觉行为控制中,森林碳汇信息量、森林碳汇价格等都是影响公众森林碳汇购买意愿的因素,但影响程度差异不大。

农牧民乳制品质量安全的风险感知、政府质量监管的信任与购买意向和行为研究

为了促进农村牧区乳制品消费市场的健康发展,本研究依据内蒙古自治区的东部、中部及西部5个盟市的544份农牧户问卷调查结果,在对农牧民乳制品质量安全的风险感知、对乳制品加工企业的信任情况、对乳制品品牌的满意度、对政府监管乳制品市场的信任度及农牧民对乳制品购买意向和行为统计描述分析的基础上,运用结构方程模型验证它们之间的关系。结果表明:农牧民对乳制品质量安全表现出一定的担忧,但对乳制品加工企业的信任情况、乳制品品牌的满意度、政府监管乳制品市场的信任度较高;此外,农牧民对乳制品有比较高的购买意向,且农牧民购买乳制品的种类以保质期较长的奶茶粉、奶粉等为主,购买种类比较单一;农牧民对乳制品质量安全的风险感知、质量水平的信任、政府监管的信任及品牌的信任均通过购买意向在1%水平上显著影响其购买行为。其中,除了风险感知极显著负向影响购买行为外,其余三个因素均正向影响购买行为。基于此,乳制品企业在产品质量的提高方面要不断下功夫,政府要加大对乳制品市场监管的力度,不断提高公信力,加大农牧区乳制品消费的宣传工作,提高农牧民对乳制品消费的信心和认知,引导农牧民对乳制品多样化的消费,以促进乳业在农牧区的可持续发展。

服务经济下网购消费者延保服务购买意向研究

延保服务因其盈利能力和风险规避属性受到电商平台和消费者的青睐。以网购消费者在线延保服务购买行为为研究对象,基于技术接受模型和计划行为理论构建研究模型,通过在线收集的610份有效数据对模型及假设进行验证分析,探索影响企业延保服务网络零售的因素,揭示相应的作用机理,为网络零售业高质量发展提供运营与政策优化方面的借鉴。研究发现:感知有用性和感知易用性对消费者延保服务购买意向均有显著的正向影响,且感知有用性的作用强度相对较大;购买态度作为中介变量能够增强感知有用性和感知易用性对延保服务购买意向的正向影响;主观规范和知觉行为控制显著正向影响消费者延保服务的购买意向,且二者作为调节变量能够分别增强感知有用性、感知易用性对延保服务购买意向的影响;感知有用性影响消费者的购买态度,进而形成消费者延保服务购买意向,是最显著的影响路径之一。

基于劝导式思维的地铁车厢空间设计策略

目的从劝导式思维出发,通过设计介入寻求合理的地铁车厢布局,借助行为导向来规避公共环境下的不良行为习惯。方法首先,梳理劝导设计和可供性作用机制的构成内涵,归纳出劝导设计与可供性的结合特性;其次,利用劝导式设计思维,探讨地铁乘客行为及其发生机制,寻找地铁车厢空间设计的劝导机会点;最后,通过调研和实地观察,找出造成车厢人流分布不均的主要因素。结果通过剖析车厢空间设计三要素,结合FBM模型和可供性作用机制,构建地铁车厢空间设计框架和劝导式设计模型,最终提出以乘客行为为中心的地铁车厢劝导式设计策略,即利用不同功能件的差异化舒适度调整区域吸引率;利用系统内部元素透明性进行路径劝导;利用视觉传达系统的符号暗示性实现行为触发。结论在车厢空间设计中引入劝导式思维,可有效缓解车厢人流分布不均的情况,为地铁空间设计改良提供了新思路。

如何打通绿色购买决策的“最后一公里”——绿色购买意向-行为转化机制分析

绿色购买是绿色消费中的重要环节,然而消费者“想而不买”可能会制约绿色消费市场的发展。目前,绿色购买行为转化的内在机理探索尚处在起步阶段,鲜有将外部购物情境与消费者内在特质结合考量的绿色购买决策研究。本研究从消费者购买绿色标签产品的临场决策情境出发,以计划行为理论和行动阶段理论为理论基础,结合节约认知努力的观点视角,探究绿色购买意向-行为之间的转化机制。研究结果表明:绿色购买意向对绿色购买行为有显著的直接影响;感知行为控制、绿色购买执行意向在绿色购买意向和行为之间具有双重、链式中介作用;节约认知努力对“绿色购买意向-感知行为控制-绿色购买执行意向-绿色购买行为”链式中介作用具有负向调节作用。相关结论拓展了计划行为理论中绿色购买的意向-行为转化机制,为绿色营销的管理实践提供了建议。

基于人体骨架的扶梯乘客异常行为识别方法

为准确识别乘客搭乘自动扶梯时的异常行为,避免安全事故的发生,提出了一种基于人体骨架的扶梯乘客异常行为识别方法。首先使用YOLOX-Tiny对视频中乘客位置进行检测,通过Alphapose算法提取骨骼关键点坐标,降低复杂背景的干扰;再使用多流膨胀3D卷积模块增强时空特征提取能力,聚合乘客骨架的全局特征;然后将其输入改进后的时空图卷积网络中提取乘客骨架信息,通过MS-TCN模块扩大接受域以增强时间特征的提取,联合人体关键点注意力模块(Key Point Attention Module,KPAM)提升网络对相似动作的关键骨架的关注度;最后通过Softmax对异常动作进行分类。采集扶梯运行现场视频制作数据集,试验结果表明,本文算法对乘客异常行为的识别精度达到96.1%,可应用于扶梯现场的视频监控系统,提高安全管理信息化水平。

基于出行链的铁路车站开通初期客流预测研究

【目的】为解决铁路车站开通初期客流预测缺乏数据支撑,以及估计不同交通方式成本来计算客流转移量结果与实际偏差较大的问题。【方法】以新开通南沿江城际铁路江阴站为例,考虑该线与既有高速及城际铁路的线位关系,基于城际出行链,依托旅客出行行为调查对区域内可选择的不同交通方式的城际出行效用进行定量计算,采用Multinominal Logit(MNL)模型,区分工作日与非工作日,结合客流分配现状对效用变量系数进行标定,据此预测南沿江城际铁路江阴站开通后发往南京、上海枢纽的客流量,同时结合城市经济和社会发展推演计算发往沿线其他站点的客流。【结果】结果表明,南沿江城际铁路江阴站的开通可以有效吸引江阴地区原本选择既有铁路、公路去往南京、上海的客流以及选择公路去往南沿江城际铁路沿线其他城市的客流。【结论】因此,南沿江城际铁路的开通能有效缓解辐射范围内既有铁路、公路的运输压力,客流预测结果还将支撑站点运力资源配置优化研究。

不同感知群体对自动驾驶汽车购买和使用意向的研究

为探讨L4级自动驾驶汽车(AV)的出行体验对受访者购买和使用意向的影响,受访者被分为体验感知较高和较低群体,在体验前和体验后,利用多项Logit模型建立不同体验感知群体AV购买和使用意向模型。研究结果显示,购买和使用AV的想法不确定程度对体验前、后的选择均产生显著影响,对于体验感知较高群体,体验后该变量的影响程度有所下降,而对于体验感知较低群体则有所增加。AV的价格与购买和使用意向之间呈现较强的正相关关系,价格的升高会增加购买和使用想法的不确定性,从而导致受访者放弃购买AV,选择使用社会共享自动驾驶汽车(SAV)。对于体验感知较高群体来说,体验后对AV行驶过程的感知提升会促进其购买并自己使用AV,而通过提高对AV出行感受和出行安全的感知,将促进他们购买AV并有偿共享给他人使用。另外影响体验感知较低群体对AV购买和使用意向的显著因素数量则明显减少。