An Application of Heterogeneous Bayesian Regression Models with Time Varying Coefficients to Explore the Relationship between Customer Satisfaction and Shareholder Value

The authors propose new Bayesian models to obtain individual-level and time-varying regression coefficients in longitudinal data involving a single observation per response unit at each time period. An application to explore the association between customer satisfaction and shareholder value is included in the paper. The Bayesian models allow the flexibility of incorporating industry and firm factors in the context of the application to help explain variations of the regression coefficients. Results from the analysis indicate that the effect of customer satisfaction on shareholder value is not homogeneous over time. The proposed methodology provides a powerful tool to explore the relationship between two important business concepts.

Purchase Analysis Based on the Relationship Between Customers and Service Providers

Although the service industry takes up a large percentage in world economies and is situated in the center of all industries,it has been pointed out that its growth rate is smaller compared to the other industries,which is partly because of its characteristic features:“amorphousness”,“simultaneity”,and“heterogeneity”.Service providers are therefore required to be experienced and have a good business sense to succeed in this field.The aim of this research is to support those who are not experienced or do not have a good business sense,using scientific approach.This research tries to present recommendation,taking customers’value and compatibilities with employees into account,and is based on the assumption that customers and employees have one-to-one contact over a period.A total of 3,447 customers and 133 employees were classified according to their philosophies,needs,and abilities.For each case,customers’purchase histories are first interrelated with the result of questionnaire,and put purchase behavior into marketing using Bayesian network.Then the HUB was examined and extracted features of the data of the questionnaire,and executed the stochastic inference to present the recommendation.This procedure enabled us to extract the features of customers’purchase behavior,and it is turned out that compatibilities of customers and employees are more important than the difference of their values and abilities.

Omni-Channel Retailing and Firm Performance from a Customer Lifetime Value Perspective

In the digital era,retailers are keen to find out whether omni-channel retailing helps improve long-term firm performance.In this paper,we employ machine learning techniques on a large consumption data set in order to measure customer lifetime value(CLV)as the basis for determining long-term firm performance,and we provide an empirical analysis of the relationship between omni-channel retailing and CLV.The results suggest that omni-channel retailing may effectively enhance CLV.Further analysis reveals that this process is influenced by heterogeneous consumer requirements and that significant differences exist in the extent to which the omni-channel transition may influence CLV depending on consumer preferences for diversity of commodities,sensitivity to the cost of contract performance,and sensitivity to warehousing costs.Hence,retailers should provide consumers with a complete portfolio of goods and services based on target consumers’heterogeneous requirements in order to increase omni-channel efficiency.

Informed Trading, Heterogeneity Investment, Liquidity Shocks and the Valuation of Credit Default Swaps

This paper explores the effect of informed trading, heterogeneity investment and liquidity shocks on the valuation of credit default swaps(CDSs). Under the condition of asymmetric information, the informed trading plays an important role in the valuation of CDS. Instruction order flow has a significant influence on CDS price.And the scope of influence changes in accordance with different time interval, company status and the size of bid-ask spread. Heterogeneity of investors seriously affects the market liquidity and subsequently affects the CDS price. The bigger heterogeneity of the investment philosophy, investment habits, investment preference and so on is the bigger risk for market liquidity, and the higher price for CDS shall be. On the contrary, the conclusion is also consistent. The effectiveness of liquidity, whether it is before or after the financial crisis, dominates the fluctuation of CDS price. The premium of liquidity accounts for 36% to 50% of the CDS price.

Ensemble Variable Selection for Naive Bayes to Improve Customer Behaviour Analysis

Executing customer analysis in a systemic way is one of the possible solutions for each enterprise to understand the behavior of consumer patterns in an efficient and in-depth manner.Further investigation of customer patterns helps thefirm to develop efficient decisions and in turn,helps to optimize the enter-prise’s business and maximizes consumer satisfaction correspondingly.To con-duct an effective assessment about the customers,Naive Bayes(also called Simple Bayes),a machine learning model is utilized.However,the efficacious of the simple Bayes model is utterly relying on the consumer data used,and the existence of uncertain and redundant attributes in the consumer data enables the simple Bayes model to attain the worst prediction in consumer data because of its presumption regarding the attributes applied.However,in practice,the NB pre-mise is not true in consumer data,and the analysis of these redundant attributes enables simple Bayes model to get poor prediction results.In this work,an ensem-ble attribute selection methodology is performed to overcome the problem with consumer data and to pick a steady uncorrelated attribute set to model with the NB classifier.In ensemble variable selection,two different strategies are applied:one is based upon data perturbation(or homogeneous ensemble,same feature selector is applied to a different subsamples derived from the same learning set)and the other one is based upon function perturbation(or heterogeneous ensemble different feature selector is utilized to the same learning set).Further-more,the feature set captured from both ensemble strategies is applied to NB indi-vidually and the outcome obtained is computed.Finally,the experimental outcomes show that the proposed ensemble strategies perform efficiently in choosing a steady attribute set and increasing NB classification performance efficiently.

Ecosystem Service Valuation of Watershed Restoration in the Shiyang River Basin under Heterogeneous Preferences

Evaluations connect ecosystem and human welfare to achieve restoration. There have been an increasing number of studies conducted on various ecosystem service assessments, but little research has focused on inland river basins playing a critical role in development in northwestern China. The distinct differences in natural endowment, socioeconomic characteristics among the upper, middle and downstream inland river basin require heterogeneity during evaluation. The objective of this study was to verify the existence of population preference heterogeneity and examine impact factors using choice experiment surveys in the Shiyang River Basin, China. A mixed logit model using data from 714 households across the entire basin estimated mean willingness to pay and the standard deviation for ecological attributes. Ordinary least squares（OLS） was employed to estimate the effects of exogenous variables on all willingness to pay estimations. The results demonstrate that ecosystem service values are heterogeneous among people. Willingness to pay is affected by personal and regional characteristics. Government involvement will be required to seek differentiated ecosystem services values among populations and facilitate public support.

协作配送中多车型和顾客时间窗对企业成本节约的影响研究

协作配送是实现企业降本增效的重要途径。传统研究多假设联盟车辆同质且未考虑顾客时间窗,但实际中联盟企业的车辆异质以及顾客对配送时效的要求普遍存在。本文考虑每个企业的多车型以及企业之间车型的差异、顾客期望时间窗,建立了以一次性生成2n-1(n为企业数量)个子联盟对应协作配送问题的数学模型,利用自适应大邻域搜索算法求解最优路径,运用Shapley值法分摊大联盟总配送成本。通过设计并求解多组算例,本文验证并探讨了各企业参与协作所实现的经济效益,重点分析了车辆多样性和顾客时间窗对大联盟及每个成员配送成本节约的影响。结果表明:在时间窗约束下,车辆装载能力不完全相同的企业协作配送能够保证货物准时送达,提高车辆平均装载率并减少49.55%~72.77%的配送成本;与大联盟中所有成员均拥有相同的车型相比,某个成员新增一类不同车型有益于减少大联盟的协作总配送成本,降低该成员在大联盟中分摊的成本及分摊比重;某个成员所服务顾客的期望时间窗数量越少或该成员的顾客期望等待时间越长时,不同顾客时间窗之间的协调程度越高,大联盟的协作总配送成本、该成员的成本分摊及分摊比重越小。

供应链客户稳定度与企业全要素生产率

文章围绕党的二十大报告提出的“着力提升产业链供应链韧性和安全水平”“着力提高全要素生产率”相关精神,利用上市公司前五大客户数据考察了供应链客户稳定度能否对企业全要素生产率产生积极影响。研究结论如下:(1)较高的客户稳定度能够显著提升企业的全要素生产率水平。(2)机制分析表明,客户稳定度提升企业全要素生产率的三条作用路径分别是促进企业稳收降本和外部融资、提高存货管理效率和促进创新。(3)异质性检验结果显示,与国有企业、资本密集型和劳动密集型企业、行业竞争程度低的企业以及客户地理距离近的企业相比,在非国有企业、技术密集型企业、行业竞争程度高的企业以及客户地理距离远的企业中,客户稳定度对全要素生产率的提升作用更大。(4)经济后果检验表明,较高的客户稳定度可以通过改善企业全要素生产率继而进一步提升企业价值。文章不但拓展了既有企业全要素生产率影响因素、客户稳定度经济后果的相关理论研究,而且所取得的一系列结论对供应链管理理论、资源基础理论以及大客户管理理论等方面的研究视角和分析框架做出了必要的补充,同时也为如何在以国内大循环为主体的新发展格局背景下,通过增强供应链韧性和稳定性来促进经济高质量发展提供了有价值的理论依据和大样本的经验证据。

Spatiotemporal Characteristics of Typical Ecosystem Services and Their Spatial Responses to Driving Factors in Ecologically Fragile Areas in Upper Yellow River,China

The identification of dominant driving factors for different ecosystem services(ESs)is crucial for ecological conservation and sustainable development.However,the spatial heterogeneity of the dominant driving factors affecting various ESs has not been adequately elucidated,particularly in ecologically fragile regions.This study employed the integrated valuation of ESs and trade-offs(InVEST)model to evaluate four ESs,namely,water yield(WY),soil conservation(SC),habitat quality(HQ),and carbon storage(CS),and then to identify the dominant driving factors of spatiotemporal differentiation of ES and further to characterize the spatial heterogeneity characteristics of the dominant driving factors in the eco-fragile areas of the upper Yellow River,China from 2000 to 2020.The results demonstrated that WY exhibited northeast-high and northwest-low patterns in the upper Yellow River region,while high values of SC and CS were distributed in central forested areas and a high value of HQ was distributed in vast grassland areas.The CS,WY,and SC exhibited decreasing trends over time.The most critical factors affecting WY,SC,HQ,and CS were the actual evapotranspiration,precipitation,slope,and normalized difference vegetation index,respectively.In addition,the effects of different factors on various ESs exhibited spatial heterogeneity.These results could provide spatial decision support for eco-protection and rehabilitation in ecologically fragile areas.

ESG(环境、社会和治理)评价、企业异质性与绿色创新——来自A股上市企业的经验证据

为深入探究ESG(环境、社会和治理)评价与企业绿色创新的内在联系与作用机制,基于A股上市企业面板数据,实证分析了ESG评价对异质性企业绿色创新的影响机制。研究表明,ESG评价通过引导企业加大创新投入进而在整体上显著促进了绿色创新;异质性分析发现,ESG评价的绿色创新效应在中小企业、非国有企业和处于成长期企业中更为明显。进一步研究发现,ESG评价不仅影响企业的策略性创新,还显著提升企业绿色创新质量;重污染行业和创新生态环境对ESG评价的绿色创新效应的影响不明显。研究结果为探索ESG评价的绿色创新效应提供参考,并为政府进一步完善相关政策、更好地推动企业绿色创新提供理论支持。

煤堆非均质分布及其自热研究

为了掌握煤堆内的非均质分布状态以及非均质煤堆的自热过程,利用颗粒动力学原理提出了基于颗粒下落堆积演化规律的堆体数值重构方法,研究了不同倾倒高度和颗粒粒径下所形成堆体的内部空隙分布情况,将所得空隙分布变化规律及与空隙关联的变量编成自定义函数、进行非均质煤自热模拟,分析非均质煤堆内部温度场、压力场、组分浓度场的变化。结果表明,空隙率随堆体内部垂直方向距离的增加而先减小后增大,而在内部相同高度的水平方向上空隙分布近乎均匀;0.55~0.95 m的倾倒高度大小变化以及1.1~1.9 cm的粒径粗细变化对堆体内部空隙率影响较小;非均质煤自燃中,高温区域逐渐缩小成靠近迎风侧、背风侧与底部接触的两个温度极高、对煤堆安全威胁最大的点。

在线大规模定制下面向异质客户的需求智能获取方法

为便捷地在线获取需求表达能力异质的众多消费类机电产品客户的定制需求,研究了一种面向异质客户的需求智能获取方法。建立了面向异质客户的需求智能获取方法的体系结构,提出了实现该体系结构的具体过程。通过获取客户的个人特征和需求情境信息、特征推理分析、模糊加权计算、置信度阈值检测、反馈与需求表达及去模糊化处理等6个步骤,为每一位客户提供定制的需求交互过程,并最终输出精确的客户需求信息。以摩托车产品为案例说明了该方法的有效性和实用性。

基于消费者行为和估值折扣差异的易逝品两期定价决策研究

基于策略消费者的行为特点构建报童模型,对消费者的估值折扣系数和选择行为影响下的零售商3种定价策略进行对比分析。分析结果表明,当第一期进入市场的消费者数量与第二期可能进入的最大消费者数量的比值大于某临界值时,若策略消费者的估值折扣系数较小,零售商应采用高价上市-低价抛售策略,第一期实行高价,第二期以较低折扣价格售出商品,使策略消费者等待到第二期购买;若估值折扣系数较大,零售商应采用高价上市-高价抛售策略。当第一期进入的消费者数量与第二期可能进入的最大消费者数量的比值较小时,零售商的定价策略受短视消费者的比例和第二期的产品可得率的大小关系的影响。

顾客价值创新的战略逻辑和基本模式

随着市场竞争的日益激烈 ,顾客需求的不断变化 ,传统的竞争战略逻辑已经不能适应企业生存与发展的要求。本文基于顾客价值创新的战略逻辑 ,提出了实现顾客价值创新的途径及基本模式。

考虑策略性顾客的动态定价和差价返还机制

由于销售期短和残值很低,季节性产品普遍采用正常销售和季末降价结合的动态定价模式。一部分顾客会预期零售商季末降价,可能等待到季末购买以获得更大的净效用,顾客的这种策略行为减少了零售商的收益。本文假设市场中同时存在策略性和短视性顾客,分析了零售商考虑策略性顾客的动态定价,以及差价返还机制对零售商定价和收益的影响。研究表明策略性顾客延迟购买影响了零售商的定价决策并使得收益减少,而差价返还机制可以消除策略性顾客的延迟购买行为,提高零售商的收益。

基于等待成本差异的顾客密集型服务策略研究

在顾客密集型服务中,服务效果同服务速度成反比,服务效率的提高受到限制,等待难以避免。而等待成本往往是顾客考虑是否选择服务的重要因素,且因人而异,因此当服务商面对单位时间等待成本不同的顾客时,该如何制定服务速度与价格才能使得收益最大化?基于M/M/1排队系统针对服务商面对单位时间等待成本不同的两类顾客情景进行研究,根据队列均衡状态下顾客对于服务的选择情况提出了四种有效策略,通过对比分析发现:当顾客潜在到达速率较小时,以单位时间等待成本较高的顾客(H顾客)为基准制定服务策略最优;而当潜在到达速率较大时,则应该以单位时间等待成本较低的顾客为基准制定策略;且随着两类顾客等待成本差距的缩小,以H顾客为基准所制定策略的适用范围也相对扩大。

CBCV模型在网络企业价值评估中的应用

文章首先综述了目前已有的网络企业价值评估研究,分析了CBCV模型的优势和当前存在的不足;在将该模型应用于网络企业价值评估前,首先从与客户相关的现金流归集、未来客户数量预测以及网络企业折现率的计算3个方面进行修正;并以合肥市的一家网络企业为例,说明了具体的评估计算过程,最后提出了几点展望。

企业估值中价值乘数的选择:基于行业差异性的研究

基于行业差异性理论分析不同行业在经济结构、经济周期、要素集约度、资本结构等方面的差异,目的在于论证行业的差异性是否会导致价值乘数的非对称性。探求不同价值乘数的行业适用性,以形成不同行业与价值乘数之间的双向匹配关系。根据要素集约度选取采掘业、建筑业、交通运输业以及信息技术业作为研究对象,在实证研究的基础上,确定价值乘数选择条件及优先等级,进而确定行业乘数。

互联网企业的价值评估——基于客户价值理论的模型研究

为了对互联网企业的价值进行有效评估,需要找到互联网企业的价值源泉。根据客户价值理论,互联网企业的价值来源在于其所掌握的客户资源,通过评估客户价值可以计量互联网企业价值,这是基于客户价值理论的互联网企业价值评估模型的理论依据。其中,单位客户收入贡献、未来客户数量预测以及权益成本的估算对模型的适用性影响很大。

创新驱动顾客价值实现的路径选择

"服务企业创新能够提升顾客满意吗?"文章基于这一问题在回顾文献的基础上构念出基于顾客价值的创新模型,并通过对不同服务行业典范企业的多案例分析进行检验和修正,结果显示:创新对顾客满意具有明显的正向促进作用,说明服务型企业进行创新是必要的,创新可成为服务型企业发展的驱动力。研究还发现,服务型企业依靠创新提升顾客满意需要具备如下条件:以需求管理为前提,以顾客价值为愿景,以价值创新为核心,以精益服务为手段。研究结果可为进一步分析服务型企业提升顾客满意提供借鉴和参考。