Exploring the core factors of online purchase decisions by building an E-Commerce network evolution model

With the continuous development of the Internet and information technology, online shopping has become a popular purchase mode. The in-depth analysis of consumer decision-making in online shopping is an important issue. Our purpose is to study how the factors of the shopping web pages corporately affect online purchase decisions and determine which are the core factors that affect consumer purchase decisions. We screen the influencing factors on the shopping webpage and deploy e-commerce network evolution based on various weight combinations of these factors to generate sales distributions of online products. By comparing these simulated sales distributions to the real data, the optimal weight of each factor is obtained. The results show that sales volume and the number of high-quality negative comments are the most important factors influencing consumers' decision-making, the number of comments and the number of comments with pictures are relatively minor factors, store type and video presentation of the products have the least impact. The optimal simulated sales distribution is very close to the real case and verifies that the introduced network evolution technology is applicable. The proposed model can be used as a uniform evaluation platform for correlational study, which is an important link in the purchase research chain.     

How to retain customers in omnichannel retailing: Considering the roles of brand experience and purchase behavior

The opportunities and challenges of omnichannel in retail industry have been widely discussed, yet despite these benefits, the key elements that constitute an effective omnichannel and how customers respond to omnichannel retailing strategies remain unclear. This research conducted online surveys to test the effects of omnichannel elements on various brand experiences and customer retention, considering the moderating role of purchase behavior. The results indicate that omnichannel elements (integration, individualization, and interaction) are generally helpful in retaining customers, through omnichannel elements influence brand experiences differently. In addition, these omnichannel elements have different influences on customer retention due to different purchase behaviors. The findings suggest that retailers can use different omnichannel strategies to attract customers’ purchases and provide insights for practitioners who want to use omnichannel strategies to deliver superior experiences for customers.     

Increase hedonic products purchase intention through livestreaming: The mediating effects of mental imagery quality and customer trust

Although online retailing is applying livestreaming to promote both hedonic and utilitarian products, the differential effectiveness of utilizing this tool across the two types of products is still unclear. With an online experiment, the study found that livestreaming (vs. traditional e-commerce) is more effective in boosting hedonic products while making no difference in increasing purchase intentions of utilitarian products. By running a moderated serial mediation analysis, the research also demonstrated the underlying mechanism that livestreaming could significantly enhance mental imagery quality and customer trust in hedonic rather than utilitarian products. Therefore, our research has discovered an important boundary condition for the livestreaming effect and also the mechanism for the success of utilizing livestreaming to boost hedonic products. Considering the indiscriminate use of livestreaming regardless of product types and the huge amounts of resources required to sustain livestreaming, the study not only provides a theoretical glimpse of where livestreaming is more effective and why, but also practical insights as to how to apply livestreaming to different types of products and how to leverage mental imagery and customer trust to achieve business growth in an online retailing context.     

提升算法对传统车险索赔频率建模模型的改进——基于我国五省交强险保单数据

广义线性模型作为非寿险定价的经典模型,在非寿险定价中得到了广泛的应用。近年来,以提升算法为代表的机器学习算法在保险领域取得了很好的效果,为保险产品定价提供了一种新的选择。本文将提升算法思想分别融入到回归树模型和广义线性模型(GLM)中去,用得到的新模型对我国车险索赔频率进行预测建模分析,并与传统的回归树模型和GLM进行比较。结果表明,加入提升算法后传统车险索赔频率建模模型的效果得到了很大的改善,并且在不存在过拟合的前提下,随着模型深度和迭代次数的增加,模型的效果也在不断优化。     

基于交易成本的消费者网络购物意愿的实证研究

首先对网络购物中的交易成本相关研究进行文献综述,在此基础上,建立网络购物中消费者交易成本影响因素的相关研究假设,运用PLS—SEM模型的研究方法,采用问卷调研获取的数据,对消费者网络购物意愿进行了实证分析。研究表明,购买频率和不确定性显著地影响交易成本,不确定的影响作用较大,并最终对购买意愿产生影响。     

一种基于遗传算法的战场频率分配方法

分析了遗传算法的原理及其在频率分配领域中的应用,提出了一种启发式战场频率 分配方法。该方法通过改进传统遗传算法的选择、交叉、变异过程来实现频率分配的特殊 用途,并借助代价函数对生成的频率分配方案进行质量评估。仿真结果表明,该方法能够在 一 定程度上提高频谱资源的使用效率,可为从事频谱管理等相关行业的技术人员提供参考。     

变频调速技术在大变幅特征水位取水泵站的应用

文章通过对广西钦州市进口资源加工区钦南片区供水工程取水泵站水泵机组选型设计进行分析,浅述变频调速技术在大变幅特征水位取水泵站的应用。     

无拍频控制技术在新一代CRH380CL型高速动车组上的应用

高速动车组技术的迅猛发展对牵引变流器的性能提出了更高的要求。在动车组传动系统中,单相脉冲整流器工作时,会在中间直流环节产生2倍于电网频率的脉动分量,该脉动分量传递到逆变器输出侧会在电机上产生拍频现象,引起转矩脉动和电机过热。     

变频器调速系统在门式起重机上的应用

随着新技术和控制系统设备的发展,变频调速技术在起重机领域得到广泛应用,为可靠调速及节能提供全新的方案。文中研究了变频调速技术在门式起重机中的应用,对变频调速系统常见故障做了归纳总结,并提出了相应的解决措施,为起重机电控系统设计及改造提供了参考。     

基于成本分析的发车频率模型在广州BRT的应用

班车的发车频率对服务水平及成本控制都起着重要作用。发车频率低,可以降低成本,但是不能满足乘客需求,会引发一系列社会问题;发车频率高,虽然给乘客提供了更好的服务,但是却大大增加了运营成本。本文将在陈文进《大众运输路线服务模式构建之研究》中提出的基于成本的公交班车派发频率模型的基础上,增加环境因素的考虑对模型进行完善。再次本文将以LINGO为工具对模型进行简单求解,并将模型应用于广州快速公交对广州BRT的发车频率进行优化。