Statistical inference for Cox proportional hazards models with a diverging number of covariates

For statistical inference on regression models with a diverging number of covariates, the existing literature typically makes sparsity assumptions on the inverse of the Fisher information matrix. Such assumptions, however, are often violated under Cox proportion hazards models, leading to biased estimates with under-coverage confidence intervals. We propose a modified debiased lasso method, which solves a series of quadratic programming problems to approximate the inverse information matrix without posing sparse matrix assumptions. We establish asymptotic results for the estimated regression coefficients when the dimension of covariates diverges with the sample size. As demonstrated by extensive simulations, our proposed method provides consistent estimates and confidence intervals with nominal coverage probabilities. The utility of the method is further demonstrated by assessing the effects of genetic markers on patients' overall survival with the Boston Lung Cancer Survival Cohort, a large-scale epidemiology study investigating mechanisms underlying the lung cancer.     

新零售渠道整合下生鲜供应链的定价与协调策略

在新零售模式下，本文针对双渠道生鲜供应链，考虑供应商与传统零售商之间的物流合作以及在此基础上的价格整合情形，基于消费者效用理论，综合考虑价格和产品新鲜度对消费者购买决策的共同影响，建立整合前后的定价和协调模型，采用线性补偿契约与收益共享契约进行协调，得到相应的最优协调策略。通过最优决策量数值模拟，对比分析三种不同程度渠道整合情形下生鲜供应链个体以及供应链系统的最优定价决策以及最优利润水平。研究发现：线上线下的物流合作会使对线性补偿量具有强势决策权的传统零售商在利润分配中占优；在进行物流整合的基础上，各供应链成员是否应开展价格整合，取决于消费者对产品时效性要求的高低以及其自身的讨价还价能力；对系统来说，渠道整合可以扩大消费者群体，提高供应链的总利润。     

多渠道零售商线上线下协同营销研究综述与展望

开展线上线下业务成为传统零售商转型的方向,但多渠道策略会引发资源抢夺,造成线上线下渠道冲突,使协同效应被替代效应抵消,多渠道零售商如何实现协同营销成为研究的热点问题.文章从协同营销概念出发,厘清零售商线下“触网”线上和线上“进军”线下两种线上线下协同营销类型,从渠道整合、企业资源、商品和服务三个视角梳理多渠道零售商线上线下协同营销策略,系统回顾多渠道零售商线上线下渠道协同绩效、营销策略契合度、顾客信任等方面研究,展望该领域未来研究方向,以期为学术界开展协同营销理论研究和多渠道零售商实践线上线下协同营销提供参考.     

The Design of Feature‐Limited Demonstration Software: Choosing the Right Features to Include

Today, software supports many important tasks in a variety of industries. In the specialized nature of these environments, a common problem faced by software vendors is to correctly signal the true value of a software product to the end users. For example, telecommunications equipment manufacturers design complex software for important functions like provisioning new users in the network. These software products automate various functions that would otherwise need to be done manually. In order to enable potential customers—telecommunications providers—to evaluate and recognize the full value of the product, equipment vendors often provide a free, feature‐limited version of the product to the customer. As the specific features included in the feature‐limited version influence whether the full product is purchased or not, it is essential that the features included in the feature‐limited version be selected judiciously. While the importance of identifying the best set of features has been well recognized, there has been little research to date that systematically addresses this fundamental business decision. This study fills this gap in the literature by providing an objective approach to the design of demonstration software. We illustrate the benefits of our approach through a case study involving the design of a feature‐limited demo for a wireless telecommunications equipment manufacturer.