Factors of Marketing Toward Customer Decision-Making in Cross-Border E-Commerce:Case Study of QD Company

Taking small cross-border e-commerce enterprise QD company as an example,this study targets customers consuming on the platform of cross-border e-commerce enterprise QD company,and the purpose is to study the marketing factors affecting customer decision-making.By combining with relevant literature,this paper preliminarily confirmed that 7Ps,Technology Acceptance Model(TAM),and customer decision-making theory as the theoretical basis,and established the theoretical model.According to the mature scale of domestic and foreign scholars to measure the research variables,with 7Ps and TAM as the independent variable,TAM perceived usefulness and ease of use as the core of the independent variable,customer decision-making as the dependent variable,in the test before the project,forming a formal questionnaire,the main data are obtained through the design and distribution of the questionnaire.Based on a large number of relevant literature,this paper examines the marketing factors influencing customer decisions in cross-border e-commerce,then identifies goals,builds models,and proposes hypotheses.According to the technical acceptance model in consumer behavior theory,select the cross-border e-commerce enterprise quantum dot platform of consumers as the research object,finally through SPSS software on cross-border consumer feedback,including descriptive statistical analysis,factor analysis,correlation analysis,regression analysis test customer satisfaction,finally found a significant positive relationship between customer decision-making and marketing mix and TAM variables.

Research of Order Allocation of E-commerce Logistics Service Supply Chain Considering Customer Evaluation

Based on the importance of customer evaluation for developing e-commerce enterprises,this paper analyzes the customer evaluation as a fuzzy variable and establishes a multi-objective mixed integer order allocation planning model by considering customer satisfaction,which maximizes customer praise and minimizes procurement cost.As the optimization goal,transaction cost is optimized for the order allocation of the secondary e-commerce logistics service supply chain.In order to defuzzify the customer evaluation,a fuzzy evaluation method is designed to transform the customer evaluation from fuzzy language evaluation to numerical measurement.Finally,the feasibility and effectiveness of the model are verified by using a specific example,and the order is made for the e-commerce enterprise.The allocation provides a theoretical reference.

Regulating Crossing Border E-commerce by SC

Crossing border e‐commerce develops rapidly because of e‐commerce development.There are three typical modes of crossing border e‐commerce,and they are B2B(business to business),B2C(business to customer),and C2C(customer to customer).With the development of social network,a new mode called C2C cross‐border e‐commerce by SC(social commerce)is occurring.This new kind of e‐commerce has several advantages,like high trust between seller and customer and personalized consumption for customers.But there are still some problems of C2C cross‐border e‐commerce by SC,which are tax evasion and no rule to regulate.To solve these problems,several measures should be taken into account.In the area of Customs Law,it should refine the standard of luggage and post package taxation.The Custom should strengthen supervision for international post package.To deal with the problem that there is no law to regulate C2C cross‐border e‐commerce by SC,Contract Law is suitable before the E‐commerce Law enacts.

Customer Tiered Purchase Forecast by Mobile Edge Computing Based on Pareto/NBD and SVR

Mobile edge computing is trending nowadays for its computation efficiency and privacy.The rapid development of e-commerce show great interest in mobile edge computing due to numerous rise of small and middle-sized enterprises(SMEs)in the internet.This paper predicts the overall sales volume of the enterprise through the classic ARIMA model,and notes that the behavior and arrival differences between the new and old customer groups will affect the accuracy of our forecasts,so we then use Pareto/NBD to explore the repeated purchases of customers at the individual level of the old customer and the SVR model to predict the arrival of new customers,thus helping the enterprise to make layered and accurate marketing of new and old customers through machine learning.In general,machine learning relies on powerful computation and storage resources,while mobile edge computing typically provides limited computation resources locally.Therefore,it is essential to combine machine learning with mobile edge computing to further promote the proliferation of data analysis among SMEs.

The Effects of B2C Interaction on Customer Loyalty

Purpose： This research attempts to examine the relationship between B2C interaction and customer loyalty in Business-to-Customer（B2C） context from a new perspective of the interactive tool.Design/methodology/approach： The scale for B2C interactive tools is of seven dimensions： efficiency, security, fulfillment, mobility, community, cultivation, and customization. A model reflecting the influences of these attributes on customer loyalty is developed and empirically examined based on data collected from 265 B2C customers. Findings： Results reveal that the fulfillment, mobility, community, and customization of B2C interactive tools can enhance customer loyalty directly and significantly. Efficiency and security, serving as the premise for possible purchase behavior, facilitate fulfillment. In addition, cultivation promotes the formation of customization, which directly strengthens customer loyalty.Research limitations： Models considering individual-level indicators and combined with classic loyalty mechanisms in B2C context may lead to a deeper understanding of the tested effects of interaction on customer loyalty.Practical implications： To strengthen B2C interaction and further cultivate loyal customers, making interactive tools more fundamental, flexible, and personalized is critical for B2C enterprises. Originality/value： This study proposes a new perspective from interactive tools when measuring the relationship between B2C interaction and customer loyalty, and offers a useful theoretical lens and reasonable explanations for investigating customer loyalty in B2C e-commerce context.

电商客服端评论话语中的态度资源及其对潜在消费者消费决策的影响

文章从跨学科视角,首先基于从淘宝网上收集的真实语料,运用评价理论分析电商客服端评论话语中态度资源的分布模式及人际意义的实现方式;进而运用消费心理学理论探讨这些语言资源是如何影响潜在消费者的消费心理和消费取向,旨在帮助消费者在网购时做出理性的消费决策。研究表明:在电商客服端评论话语(包括好评、中评和差评)里使用的态度资源中,鉴赏资源所占比例最高,其次是情感资源,最后是判断资源;评价资源不仅体现在词汇层面,也体现在小句层面。这些态度资源与潜在消费者的消费心理、消费取向及消费决策密切相关,可以提供有关商品和服务的参考信息。消费者在网购时应正确解读这些评价资源,从而做出理性的消费决策。

基于中差评内容的酒店顾客满意度研究

信息时代下,网络线上产品销售所带动的在线点评数量也呈爆炸式增长,在线点评数据比传统渠道数据更方便获取,且能真实地反映酒店的顾客满意度情况,利于酒店更好地掌握顾客需求,从而作出有效对策,提高管理水平。基于此,以太原酒店网络评价的中、差内容为研究对象,通过分析客户满意度影响因子,得出太原市酒店的客户满意度现状,再通过分析酒店在线点评的中评、差评内容,从设施、服务、卫生三个方面提出改进顾客满意度的具体对策和建议,具有一定的可操作性和借鉴意义。

质量:企业持续发展的保证——从符合客户需求出发谈造纸企业的永续经营

论述了金东纸业质量管理的成功经验。从符合客户需求出发,以构筑企业内部满意度为切入点,来策划企业的战略决策,识别企业的关键过程,变更企业的组织形态,统筹企业的资源配置,进行有效地持续改善,从而达到卓越绩效的实现。并介绍了当代流行的质量管理方法在造纸企业的运用。

A Brief Review for E- Commerce and the Critical Success Factors

Along with the rapid development of information technologies, traditional trade has moved to electronic area. Today, many business activities are performed in electronic environment. Since electronic commerce is rapid and easily reachable, it has begun to attract much more attention by consumers and businesses over time. In this study, a brief review about e-commerce is provided. The main aim is to examine the hot topic of e-commerce with different aspects. The increasing importance of e-commerce is presented by providing statistical support which shows a dramatic increase in total e-commerce sales worldwide. Tools, types, payment methods, and critical success factors of e-commerce are investigated. Eight different tools which can be used in e-commerce are explained. Seven types of e-commerce are classified. In addition, nine payment methods of e-commerce are elaborated. Moreover, three main critical success factors including eight sub-factors are structured in a hierarchical form to aid the companies in e-commerce. Depending on these critical success factors, this study aims to set a well-organized base in order to decide the best e-commerce company in further studies.

Same-day delivery time-guarantee problem in online retail

This study introduces the same-day delivery time-guarantee(SDDTG)problem for supporting online retail.In the SDDTG,orders are placed online and are processed and delivered from a depot to customer locations in the same day.The problem seeks optimal delivery time guarantees to offer customers as they consider making purchases to increase purchase decision likelihood while accounting for delivery-related,supply-side costs that can affect profits.Time guarantees are decision variables rather than parameters(as is typical)and are designed around anticipated customer satisfaction levels and purchase likelihoods.Delivery deadlines are not merely given to customers once they make their purchases,but rather the attractiveness of the offered delivery guarantees affects whether they make their purchases,i.e.,whether demand is realized.The problem is conceptualized as a multistage,stochastic,mixed-integer program in which uncertainties associated with customer reaction to delivery time guarantee offers and their arrival over time are captured.Given a shrinking horizon over a fixed planning horizon,the multi-stage program is approximated by a series of two-stage programs.A parallelized progressive hedging solution methodology is proposed and insights from its application on a case study.The problem recognizes tradeoffs between meeting promised delivery times and capturing the market.

User Modeling for Personalized Recommender Systems

This paper models a user's interest and value related characteristics based on the extension by using neural networks and econometric techniques to the concept of user model in recommender systems. A two-dimensional taxonomy of user model was proposed in terms of the content and persistence of user characteristics. A user interest model and a customer lifetime value model were developed for the proposed taxonomy framework, to capture the time-dependent evolving nature of user's interests and his/her long-term profitability. The proposed models were empirically validated by using real customer data from a bee product company in health care industry. The experimental results show that these models provide effective assistant tools for the company to target its most valuable customers and implement one-to-one personalized services.