An Empirical Investigation of the “Dynamic McFadden” Model of Purchase Timing and Brand Choice: Implications for Market Structure

Purchase timing and brand-choice decisions of households are jointly investigated using the “dynamic McFadden” model of Heckman and Singer. The hazard of brand purchase is decomposed into the category purchase hazard and the probability of brand choice conditional on category purchase. The former is modeled using the hazard-function approach and the latter using a logit model. Unobserved heterogeneity in brand preferences, marketing effects, and baseline hazard parameters is accounted for in the empirical analysis. The distribution of preference heterogeneity identifies the locations of brands in multiattribute perceptual space and the distribution of attribute importance weights across households.     

Purchase timing models in marketing: a review

In this work we review various approaches to modeling the purchase behavior of consumers in marketing. Special emphasis is given to the timing of purchases. We also discuss in detail a new approach which models the hazard function in a flexible dynamic way thus yielding self-exciting phenomena. In particular our approach is able to incorporate seasonal and advertising effects and past purchase decisions. The method is applied to panel data for fast moving consumer goods.     

Bayesian Inference for Assessing Effects of Email Marketing Campaigns

Email marketing has been an increasingly important tool for today’s businesses. In this article, we propose a counting-process-based Bayesian method for quantifying the effectiveness of email marketing campaigns in conjunction with customer characteristics. Our model explicitly addresses the seasonality of data, accounts for the impact of customer characteristics on their purchasing behavior, and evaluates effects of email offers as well as their interactions with customer characteristics. Using the proposed method, together with a propensity-score-based unit-matching technique for alleviating potential confounding, we analyze a large email marketing dataset of an online ticket marketplace to evaluate the short- and long-term effectiveness of their email campaigns. It is shown that email offers can increase customer purchase rate both immediately and during a longer term. Customers’ characteristics such as length of shopping history, purchase recency, average ticket price, average ticket count, and number of genres purchased also affect customers’ purchase rate. A strong positive interaction is uncovered between email offer and purchase recency, suggesting that customers who have been inactive recently are more likely to take advantage of promotional offers. Supplementary materials for this article are available online.     

商品房限购政策的实体经济发展效应研究

本文依据2014年10月至2017年11月16个“非同期”限购城市和29个非限购城市的面板数据,利用广义合成控制法研究了房地产市场限购政策调控商品房价格、促进实体经济发展的政策效应。研究发现：限购政策能够有效地抑制商品房价格过快上涨,政策效应因商品房建筑面积和城市规模等特征存在差异性;同时发现了房地产限购政策与实体经济发展相关联的典型事实,并证实了限购政策对支持实体经济发展存在较显著的“回馈效应”,特别是由限购政策产生的转移投资对实体经济产出存在约10个月的滞后期。     

Choice Behavior Under Time-Variant Quality

In past studies of consumer loyalty changes in brand attributes over time were generally unobservable and treated as additional model parameters. In this study we consider ski resorts, for which observable quality attributes change frequently. Using a repeated-purchase model with observed time-variant brand attributes, indicators for state dependence, and individual heterogeneity, we show that purchase history and time-variant site characteristics have a significant and offsetting effect on repurchase decisions. This suggests a third category of consumer along with habit formers and variety seekers, the “play-it-by-ear” type, who, unaffected by purchase history, moves across brands in pursuit of high quality.     

Modeling Heterogeneity and State Dependence in Consumer Choice Behavior

In frequently-purchased-consumer-goods markets, consumer brand choices exhibit substantial persistence across purchase occasions. In this article, I estimate a choice model that admits of both heterogeneity in preferences and true state dependence as sources of this persistence, using Nielsen scanner data on ketchup. I find evidence for true state dependence in the choice process, even after controlling for a rich heterogeneity structure. Simulation of the model indicates that the long-term effect of a promotion-induced purchase on future purchase probabilities is positive but small.     

食品标签信息对消费者购买决策的影响研究——以婴幼儿食品为例

基于Hicks消费者剩余的CV形式,构建信息关注度、信息源信任度、信息充分度的Logit食品标签信息影响决策模型.通过在北京市发放问卷并回收、统计数据及分析,研究发现:消费者在购买婴幼儿食品时,对食品标签上的食品生产日期和保质期、营养成分、配料清单、食用指导注意等信息的关注度高,影响显著;对食品品牌、生产厂家及厂址、使用方法及贮藏、安全标识等信息关注度低,影响不显著;消费者对政府机构、婴幼儿医师和学者、亲朋及名人代言等信息源的信任度高,对购买决策影响显著;消费者对非政府机构和食品企业等信息源的信任度低,对购买决策影响不显著;食品标签信息充分度对消费者获得高质量信息、降低风险和提高决策准确度等起到的作用很大;消费者的性别、年龄、收入、受教育程度等对购买决策影响显著;相对于女性而言,食品标签信息对男性消费者的购买决策更有影响.     

Unit-Root Tests and the Statistical Pitfalls of Seasonal Adjustment: The Case of U.S. Postwar Real Gross National Product

An often-used scenario in marketing is that of individuals purchasing in a Poisson manner with their purchasing rates distributed gamma across the population of customers. Ehrenberg (1959) introduced the marketing community to this story and the resulting negative binomial distribution (NBD), and during the past 30 years the NBD model has been shown to work quite well. But the basic gamma/Poisson assumptions lack some face validity. In many product categories, customers purchase more regularly than the exponential. There are some individuals who will never purchase. The purpose of this article is to review briefly the literature that addresses these and other issues. The tractable results presented arise when the basic gamma/Poisson assumptions are relaxed one issue at a time. Some conjectures will be made about the robustness of the NBD when multiple deviations occur together. The NBD may work, but there are still opportunities for working on variations of the NBD theme.     

MULTILEVEL DISCRETE‐TIME EVENT HISTORY MODELS WITH APPLICATIONS TO THE ANALYSIS OF RECURRENT EMPLOYMENT TRANSITIONS

Data on the timing of events such as births, residential moves and changes in employment status are collected in many longitudinal surveys. These data often have a highly complex structure, with events of several types occurring repeatedly over time to an individual and interdependences between different event processes (e.g. births and employment transitions). The aim of this paper is to review a general class of multilevel discrete‐time event history models for handling recurrent events and transitions between multiple states. It is also shown how standard methods can be extended to allow for time‐varying covariates that are outcomes of an event process that is jointly determined with the process of interest. The considerable potential of these methods for studying transitions through the life course is illustrated in analyses of the effect of the presence and age of children on women's employment transitions, using data from the British Household Panel Survey.     

外汇占款对我国货币政策调控影响的实证研究

 经济对外开放度的提高会使一国货币政策的有效性面临挑战,那么这种影响机制是通过何种方式发生的呢？又是如何传导的呢？本文以货币政策信贷观的银行贷款渠道为理论基础,定量解析了2005年人民币汇率形成机制改革以来外汇占款对其调控效果的影响。文章运用时间序列分析方法在国内首次构建了一个SVAR模型并通过约束识别了其中外汇占款的结构冲击,进而定量解析了外汇占款从货币到信贷这一传导环节对央行货币政策调控的影响程度,脉冲响应函数和方差分解均表明外汇占款的增加在长期内对基础货币、广义货币和金融机构贷款有扩张效应,且金融机构贷款余额对基础货币余额的弹性其中很大一部分是外汇占款引致的。这表明,由于存在三元悖论,开放条件下我国的货币政策的独立性受到较大影响,货币政策的实施效果受到因外部经济失衡所导致的外汇占款的影响,因此,货币政策的实施应当充分关注外汇占款的扩张性效应,并采取有效措施提高货币政策的有效性。     

消费者趋近动机对绿色产品购买意向的影响机制——基于PLS-SEM模型的研究

通过一个可调节变量模型解释消费者趋近动机对绿色产品购买意向的影响机制,构建不同环境知识水平下的消费者趋近动机—绿色产品购买意向模型。采用偏最小二乘回归结构方程模型(PLS-SEM)对762份调查问卷进行分析,研究发现,趋近动机对绿色产品购买意向和消费者创新性具有显著的正向影响;消费者创新性在趋近动机和绿色产品购买意向间起部分中介作用;环境知识在趋近动机、消费者创新性与绿色产品购买意向间起负向的可调节中介作用。     

The complexity of school and neighbourhood effects and movements of pupils on school differences in models of educational achievement

Summary.  Traditional studies of school differences in educational achievement use multilevel modelling techniques to take into account the nesting of pupils within schools. However, educational data are known to have more complex non-hierarchical structures. The potential importance of such structures is apparent when considering the effect of pupil mobility during secondary schooling on educational achievement. Movements of pupils between schools suggest that we should model pupils as belonging to the series of schools that are attended and not just their final school. Since these school moves are strongly linked to residential moves, it is important to explore additionally whether achievement is also affected by the history of neighbourhoods that are lived in. Using the national pupil database, this paper combines multiple membership and cross-classified multilevel models to explore simultaneously the relationships between secondary school, primary school, neighbourhood and educational achievement. The results show a negative relationship between pupil mobility and achievement, the strength of which depends greatly on the nature and timing of these moves. Accounting for pupil mobility also reveals that schools and neighbourhoods are more important than shown by previous analysis. A strong primary school effect appears to last long after a child has left that phase of schooling. The additional effect of neighbourhoods, in contrast, is small. Crucially, the rank order of school effects across all types of pupil is sensitive to whether we account for the complexity of the multilevel data structure.     

交易成本视角下B2C电子商务网络购物的感知风险研究

中国绝大多数网民并不通过网络进行购物,因为消费者对网络购物的感知风险太高。以交易成本理论为视角,在对网络购物的感知风险进行文献综述的基础上,提出消费者感知的各种交易成本对感知风险和购买意愿影响的研究假设,通过实地调研收集资料,对假设进行验证。实证分析结果表明,消费者网络购物感知的学习成本、搜索成本、时间成本、货币成本和风险成本影响感知风险以及最终购买意愿,企业可以通过降低消费者感知的各种交易成本降低感知风险。     

PubPredict: Prediction of progression and survival in oncology leveraging publications and early efficacy data

In oncology/hematology early phase clinical trials, efficacies were often observed in terms of response rate, depth, timing, and duration. However, the true clinical benefits that eventually support registrational purpose are progression-free survival (PFS) and/or overall survival (OS), the follow-up of which are typically not long enough in early phase trials. This gap imposes challenges in strategies for late phase drug development. In this article, we tackle the question by leveraging published study to establish a quantitative link between early efficacy outcomes and late phase efficacy endpoints. We used solid tumor cancer as disease model. We modeled the disease course of a RECISTv1.1 assessed solid tumor with a continuous Markov chain (CMC) model. We parameterize the transition intensity matrix of a CMC model based on published aggregate-level summary statistics, and then simulate subject-level time-to-event data. The simulated data is shown to have good approximation to published studies. PFS and/or OS could be predicted with the transition intensity matrix modified given clinical knowledge to reflect various assumptions on response rate, depth, timing, and duration. The authors have built a R shiny application named PubPredict, the tool implements the algorithm described above and allows customized features including multiple response levels, treatment crossover and varying follow-up duration. This toolset has been applied to advise phase 3 trial design when only early efficacy data are available from phase 1 or 2 studies.     

The impact of education on third births. A multilevel discrete-time hazard analysis

We propose to use multilevel discrete-time hazard models to assess the impact of societal and individual level covariates on the timing and occurrence of third births. We focus mainly on the impact of educational attainment on third births across 15 European countries. From the analysis in this paper, the effect of education on the propensity to have a third child is found to be negative. This education effect is not significantly weakened by the Nordic countries, but living in Scandinavia does increase the hazard for a third birth.     

A dynamic multiple-variety choice adaption model

The choice of a product on one purchase occasion by one consumer could be multiple varieties and influenced by past usage experience of this product. To mimic the real situation, this article proposes a new dynamic multiple-variety choice (DMC) model which incorporates quantitative and qualitative dynamics into an additive utility function. This model exhibits three major features of consumer purchase behavior: more than one variety purchased, learning behavior from use experience, and forgetting with the passage of time. All these are achieved by combining a simultaneous demand model with Bayesian learning theory embedded in an exponential function. The model is tested and validated using Hong Kong television viewing data. Empirical results show that including Bayesian learning in a multiple-choice model significantly improves model performance and prediction accuracy, and consideration of the effect of forgetting when studying learning behavior renders the Bayesian learning model much more accurate in practical application.     

Regularity in individual shopping trips: implications for duration models in marketing

Most models for purchase-timing behavior of households do not take into account that many households have regular and non-shopping days. We propose a statistical model for purchase timing that exploits information on the shopping days of households. The model is formulated in a counting process framework that counts the recurrent purchases for each household over (calendar) time. In our empirical application of yogurt and detergent purchases from the ERIM1 The data can be found at http://gsbww.uchicago.edu/research/mkt/Databases/ERIM/ERIM.html View all notes database, we show that calendar time effects and regular and non-shopping days are important features to include in models for purchase-timing behavior. We find, for instance, that for these product categories the probability of purchasing is 50–60% higher on Saturdays and 70% higher on regular shopping days. We highlight the managerial implications of these model features by simulating some promotional actions.     

Revisiting calendar effects in Malaysian finance stocks market: Evidence from threshold GARCH (TGARCH) model

Recent research reveals that calendar effects have largely disappeared from stock markets. However, majority of the past studies focus on stock markets at the aggregate level but do not provide firm-level evidence. Therefore, this study investigates day-of-the-week and month-of-the-year effects in Malaysian finance stocks market for the period 1/1/1997–31/12/2014. The empirical results from threshold GARCH (TGARCH) model suggest that certain daily and monthly seasonality effects are prevalent along with asymmetric news effect. The findings of study indicate inefficiency in the weak-form sense, implying that it is possible for investors to obtain the observed abnormal returns by using timing strategies.     

中国城市居民婴幼儿奶粉品牌选购行为研究——以北京市为例

以北京市城市消费者为调查对象,运用统计描述法和Logit回归模型,分析消费者对不同品牌婴幼儿奶粉的选购行为及其影响因素。研究结果表明:与国内婴幼儿奶粉品牌相比,国外品牌占据明显优势,82.7%的消费者购买国外品牌;从消费者自身的认知出发,质量安全是其购买国外品牌的主要原因。Logit模型回归结果表明,风险感知、收入、家中小孩数和性别是影响消费者品牌选购的主要影响因素。     

Grouping Tests for Misspecification: An Application to Housing Demand

We consider several grouping tests for regression misspecification, with reference to housing-demand function estimation. We compare three existing test procedures, demonstrate modifications necessary in most applications, and propose a fourth test to distinguish between two categories of potential specification error. The test procedures are evaluated in artificial simulations of alternative errors. Finally, we apply the tests to FHA home purchase data. We reject the hypothesis that household and grouped regressions differ only by sampling error or random mismeasurement of household income or price. Our results have implications for choices among test procedures and interpretations of previous housing-demand analysis.