Convenience,Price, Product

Abstract

This study examines the factors motivating consumers' purchases of specialty food and beverage products via the Internet. While convenience is often cited as a motivating factor, price and product selection have also been identified. This study considered convenience in terms of time, space, and effort. It also identifies several specific sub-categories for price and products. Among respondents who had made a recent online purchase, convenience-related issues were most frequently cited as being relevant to the purchase decision. Product-related factors were important for nearly one-third of the respondents. Price was of relatively little importance.     

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.     

The effect of shopping goals and in-store mobile device use on purchase outcomes in brick-and-mortar stores

The present study examines the effect of using a mobile device on search and evaluation by a shopper in a brick-and-mortar store. A conceptual model that proposes inter-relationships between shopping goals, the amount and type of in-store mobile device use, and purchase outcomes is developed. Data from a national quota sample of 1034 mobile shoppers is used to test hypotheses derived from the proposed model. The findings provide several new insights into the impact of in-store mobile device use on the consumer decision journey in a brick-and-mortar store. Depending upon the shopping goals of the consumer, the use of a mobile device by shoppers in a brick-and-mortar store can either decrease or increase search, lead to more deferred purchases or in-store-now purchases, and more online or physical store purchases. The study is among the first to model the pathway to purchase for mobile device assisted shoppers in brick-and-mortar stores.     

Uniform or spatially differentiated? Pricing Strategies for Information Goods under simultaneous and sequential decision-making in multi-market context

Product pricing has been one of the central issues in the field of marketing and consumer services for managers and researchers alike. However, pricing of information goods has not been paid much attention in literature. For information goods the marginal costs of production and transportation of information goods (online movies, video games, etc.) is almost zero. Hence, the pricing decisions need to be thought of purely in competitive profit maximizing terms. This paper proposes mechanisms for managers to evaluate and base their pricing decisions on rational frameworks that takes into account various situations when they enter a new market and when they are incumbent in a new market. This paper addresses the research gap of spatially differentiated pricing strategy for information goods that has not been studied in literature so far. We create stylized theoretical models under both, sequential and simultaneous decision-making conditions. We determine the equilibrium price and the equilibrium profit for the two firms for each of the four possible scenarios based on their pricing strategies. Our analysis reveals that the dominance of one pricing strategy over the other depends on product differentiation factor capturing joint effect of the product substitutability and consumer's price sensitivity under sequential decision making and the market size along with consumer's price sensitivity for simultaneous decision making. As an extension, we propose a generalized model demonstrating the uniform and spatially differentiated pricing strategies of the firms under simultaneous and sequential selection for multiple domestic and international markets.     

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Stacking模型融合的店铺销量预测

为了实现企业产品销量预估,提高生产供应的准确性与效率,提出了基于Stacking模型的融合算法进行销量预测。算法设计了两层堆叠的模型结构,初级学习器采用随机森林、支持向量回归、差分整合移动平均自回归、轻量级梯度提升机器和门控循环单元5种单模型,将分类与回归树作为次级学习器构成Stacking融合模型,并对数据进行了预测。预测结果显示,使用Stacking模型融合后得到了较好的预测结果,比单模型中效果最好的模型的均方根误差更小,平均绝对误差更小,决定系数值更大,表明Stacking融合模型的预测准确率更高。所设计模型可用于对企业店铺的产品销量进行预测,帮助企业更好地安排生产、营销活动,为减少库存、缩短生产销售周期提供数据支持,对企业生产决策有一定的参考价值。     

信托受益权登记背景下的信托产品销售决策变化及影响——基于不同渠道偏好和成本的视角

信托受益权的登记细则出台及国内信托受益权账户系统的上线,对信托产品的销售渠道产生影响。通过模型构建,研究新制度背景下服务水平变化对信托公司销售成本的影响,并推导出直销和代销两种渠道的市场份额会发生变化,信托公司直销的市场份额将增加,由第三方财富公司代销的市场份额将逐步减小。销售渠道的改变会降低信托融资的总成本,从而会对信托业以及整个金融监管模式产生积极影响。     

Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models

In this paper we propose two efficient techniques which allow one to compute the price of American basket options. In particular, we consider a basket of assets that follow a multi-dimensional Black–Scholes dynamics. The proposed techniques, called GPR Tree (GRP-Tree) and GPR Exact Integration (GPR-EI), are both based on Machine Learning, exploited together with binomial trees or with a closed form formula for integration. Moreover, these two methods solve the backward dynamic programing problem considering a Bermudan approximation of the American option. On the exercise dates, the value of the option is first computed as the maximum between the exercise value and the continuation value and then approximated by means of Gaussian Process Regression. The two methods mainly differ in the approach used to compute the continuation value: a single step of the binomial tree or integration according to the probability density of the process. Numerical results show that these two methods are accurate and reliable in handling American options on very large baskets of assets. Moreover we also consider the rough Bergomi model, which provides stochastic volatility with memory. Despite that this model is only bidimensional, the whole history of the process impacts on the price, and how to handle all this information is not obvious at all. To this aim, we present how to adapt the GPR-Tree and GPR-EI methods and we focus on pricing American options in this non-Markovian framework.     

基于改进TOPSIS法的供应商选择模型研究

为有效地帮助企业快速找到合适的供应商合作伙伴,采用直觉模糊集、评分函数等方法对TOPSIS评估法进行优化,并以此为基础建立了一种供应商选择模型。首先,采集和评估供应商的产品质量、产品价格、产品交货的可靠性、供应位置、财务情况、库存水平、劳资关系、发展能力和技术能力等相关信息,由专家给出主观评估信息,汇总为综合属性值;然后,通过直觉模糊熵确定各评估指标的权重;最后,综合考虑供应商选择决策过程中的多个目标和标准,应用改进TOPSIS法的对供应商进行分类选择。结果显示,基于改进TOPSIS法的供应商选择模型能够较准确地反映出各供应商的真实水平和对企业的潜在价值,可以有效地解决不确定条件下对供应商的选择问题,提高了供应商选择结果的可靠性。改进后的模型简便易行,具有良好的稳定性,对于合理制定企业供应商选择标准以及进一步优化决策模型具有一定的借鉴意义。     

后金融危机时代股票超额收益率影响因素的探索

运用判别分析法和决策树模型对上证180的成分股是否可以获得超额收益率及其影响因素进行了分析,并将两种方法的分析结果进行了对比。结果表明：两种方法都可以对上市公司是否可以获得超额收益进行分辨,并且可以找出影响因素。但是从两种模型的结果来看,决策树模型要明显优于判别分析法。从我们的分析样本来看,对企业是否可以获得超额收益率的影响因素主要有：市盈率、市净率、息税折旧摊销前利润/营业总收入等。在实际中,通过这两种方法,投资者可以寻找出那些具有超额收益率的股票进行投资,从而使得自身的投资结果优于大盘。