Analyzing the dependences of multi-category purchases on interactions of marketing variables

We extend the usual specification of the multivariate probit model frequently used to analyze multi-category purchase incidence data by introducing interaction effects between marketing variables. Models are estimated by a Markov Chain Monte Carlo simulation method using 24,047 shopping visits made by a random sample of 1500 households in one specific grocery store over a one year period. Our data refer to a total of 25 food and non-food product categories and include socio-demographic household attributes in addition to purchases and marketing variables. Information criteria agree on the superiority of the extended specification. Estimation results demonstrate that many interaction effects are erroneously attributed to the main effects of marketing variables if one applies the usual specification instead. We derive managerial implications with respect to sales revenue by stochastic simulation. If managers base decisions on the usual specification in spite of its worse statistical performance, they run the risk to overestimate sales revenue increases due to sales promotion activities.     

A data mining framework for targeted category promotions

This research presents a new approach to derive recommendations for segment-specific, targeted marketing campaigns on the product category level. The proposed methodological framework serves as a decision support tool for customer relationship managers or direct marketers to select attractive product categories for their target marketing efforts, such as segment-specific rewards in loyalty programs, cross-merchandising activities, targeted direct mailings, customized supplements in catalogues, or customized promotions. The proposed methodology requires customers’ multi-category purchase histories as input data and proceeds in a stepwise manner. It combines various data compression techniques and integrates an optimization approach which suggests candidate product categories for segment-specific targeted marketing such that cross-category spillover effects for non-promoted categories are maximized. To demonstrate the empirical performance of our proposed procedure, we examine the transactions from a real-world loyalty program of a major grocery retailer. A simple scenario-based analysis using promotion responsiveness reported in previous empirical studies and prior experience by domain experts suggests that targeted promotions might boost profitability between 15 % and 128 % relative to an undifferentiated standard campaign.     

Optimal and Heuristic Decision Strategies for Integrated Production and Marketing Planning

In this study we examine the effects of integrating production and marketing decisions for a short- to medium-range planning horizon in a profit maximizing firm. We formulate two models for determining price, marketing expenditure, demand or production volume, and lot size for a single product with stable demand when economies of scale are present. The full integration (FI) model simultaneously determines all the decisions involved, while the partial integration (PI) model separates the lot sizing decision from the others, as happens frequently in practice. Geometric programming (GP) techniques and marginal analysis are used to compare FI and PI, and obtain important managerial implications regarding the two models.     

A parsimonious multivariate poisson model for market basket analysis

Intensified research on multivariate Poisson models offers new opportunities for the analysis of purchase quantities in market basket data. The investigation of positive or negative correlations in quantity decisions among product categories facilitates a deeper understanding of consumer purchase behavior. The applied multivariate log-normal Poisson model introduces interdependencies between categories with multivariate normal-distributed latent effects by means of a covariance matrix. As the size of this covariance matrix depends on the number of categories in the model, its ation may become tedious. Furthermore, we assume that quantity decisions do not interact for all pairs of categories. That is why we propose to use covariance selection to derive a parsimonious representation of the correlation structure. For two market basket data sets, we show that the vast majority of off-diagonal elements in the covariance matrix are irrelevant. For a data set with product categories, the model with a partly restricted covariance matrix achieves a better fit to the holdout data than the model with full covariance matrix. For a data set with subcategories of the broader category beverage, the proposed model with restricted covariance outperforms the model with full covariance matrix even on the calibration data. We conclude that interactions of quantity decisions are overall the exception, even for complements-in-use.     

城市营销过程中的广告效用模型研究

借鉴传统产品广告效果模型的研究成果,基于城市产品内涵以及宣传途径的特点,构建了两类比较重要的城市营销过程中的"真实"广告效果模型:第一,不区分所选用的广告媒介时的情况;第二,严格区分所选用的广告媒介时的情况。主要结论为:对单一广告媒介而言,城市广告效应模型同普通产品广告效应模型形式存在重大差异;对分散广告媒介而言,广告效应取决于媒体之间的交互影响。     

Utility‐consistent Brand Demand Systems with Endogenous Category Consumption: Principles and Marketing Applications*

This paper introduces the design and implementation of utility‐consistent, brand, and category demand systems. It extends formal demand analysis to the area of brand and category demand, which directly concerns marketing researchers and managers. The proposed brand demand system is a set of interrelated demand functions that are derived explicitly from a utility function describing consumer preferences. The model generalizes by the integration of category expenditures, which are determined endogenously. The theoretical plausibility of the proposed demand model is demonstrated first and, subsequently, brand and category level systems are derived. Econometric methods for estimating the systems are also developed and illustrated in empirical data. The results yield empirically determined, quantitative insights into the structure of consumer demand for brands and product categories. The proposed approach has the attractive feature of structuring the interdependencies of consumer decisions and ensuring an explicit role for theory in applied research.     

Optimal stimulation level theory, exploratory consumer behaviour and product adoption: an analysis of underlying structures across product categories

Research of the last decades focused on answering several questions in view of optimum stimulation theory. Which variables do influence general explorative tendencies such as risk taking, variety seeking, or curiosity-motivated behaviour and how do the general explorative tendencies effect the willingness to choose new or familiar products on a repurchase occasion? The approach of this research is the attempt to analyse a wide range of variables, which have successfully been tested to influence innovative behaviour, within one simultaneous model. This research is applied across different product-categories. It is confirming the nomological validity of OSL-theory including some contextual variables by attesting a principal consistency between all (six) models that have been established throughout the range of several examined product categories. The parameters between inherent factors do not contradict when comparing the single models with each other, parameter values do only differ slightly according to category-specific peculiarities. As a consequence of these results, an overall fairly good picture is drawn of what is behind the keenness for innovations of early adopters in general (regardless of the product category).     

Sharing Rule Identification for General Collective Consumption Models

We propose a method to set identify bounds on the sharing rule for a general collective household consumption model. Unlike the effects of distribution factors, the level of the sharing rule cannot be uniquely identified without strong assumptions on preferences across households. Our new results show that, though not point identified without these assumptions, strong bounds on the sharing rule can be obtained. We get these bounds by applying revealed preference restrictions implied by the collective model to the household's continuous aggregate demand functions. We obtain informative bounds even if nothing is known about whether each good is public, private, or assignable within the household, though having such information tightens the bounds. We apply our method to US PSID data, obtaining narrow bounds that yield useful conclusions regarding the effects of income and wages on intrahousehold resource sharing, and on the prevalence of individual (as opposed to household level) poverty.     

Household‐Level Coastal Adaptation and Its Drivers: A Systematic Case Study Review

Evidence‐based information on household‐level adaptation is an important element of integrated management of vulnerable coastal regions. A growing number of empirical studies deal with household‐level adaptation at the coast in different regions. This article provides a systematic review of these studies. We analyze studies according to how households in different parts of the world are currently adapting, or how they are intending to adapt, and identify explanatory factors for adaptation behavior and intention. We find that households implement a broad range of adaptation measures and that adaptation behavior is explained by individual factors such as socioeconomic and cognitive variables, experience, and perceived responsibilities. Nonpersonal characteristics have also been used to explain adaptation behavior and intention but have not been extensively investigated. Few studies employ qualitative research methods and use inductive approaches as well as models stemming from behavioral economics. Our findings suggest that coastal risk management policies should communicate the efficacy of household‐level adaptation, in addition to information about flood risk, in order to encourage coastal households in their adaptation activities. In this context, we discuss the role of resources and responsibility of households for their adaptation behavior. We describe the lessons learnt and formulate a research agenda on household‐level adaptation to coastal flood risk. In practice, coastal risk management policies should further promote individually driven adaptation by integrating it in adaptation strategies and processes.     

Farms,Families, and Markets: New Evidence on Completeness of Markets in Agricultural Settings

The farm household model has played a central role in improving the understanding of small‐scale agricultural households and non‐farm enterprises. Under the assumptions that all current and future markets exist and that farmers treat all prices as given, the model simplifies households' simultaneous production and consumption decisions into a recursive form in which production can be treated as independent of preferences of household members. These assumptions, which are the foundation of a large literature in labor and development, have been tested and not rejected in several important studies including Benjamin (1992). Using multiple waves of longitudinal survey data from Central Java, Indonesia, this paper tests a key prediction of the recursive model: demand for farm labor is unrelated to the demographic composition of the farm household. The prediction is unambiguously rejected. The rejection cannot be explained by contamination due to unobserved heterogeneity that is fixed at the farm level, local area shocks, or farm‐specific shocks that affect changes in household composition and farm labor demand. We conclude that the recursive form of the farm household model is not consistent with the data. Developing empirically tractable models of farm households when markets are incomplete remains an important challenge.     

消费者退货对在线零售商促销与合同设计的影响研究

针对由制造商和在线零售商组成的供应链系统，在存在消费者退货情形下，考虑在线零售商在线上渠道提供促销与退款保证服务，其中在线零售商促销成本为其私有信息，建立了信息不对称下的供应链博弈模型，研究了在线零售商的最优促销策略与供应链合同设计问题；进而分析了不对称信息对供应链均衡的影响，考察了退款保证对供应双方期望利润、信息价值以及消费者剩余的影响。研究发现，当制造商在决策合同参数（设计合同）时，需要在在线零售商信息租金与供应链系统绩效损失之间进行权衡；若满足一定条件，制造商和在线零售商之间进行谈判并能够实现信息共享而分享整个系统的利润；当退货产品总是会给供应链成员造成损失时，退款保证会导致制造商和零售商期望利润的损失，但在一定条件下却能提升消费者剩余。     

The influence of stimulus ambiguity on category and attitude formation

Existing research on categorical ambiguity has mostly examined how consumers assimilate new products into familiar product categories. Extending these findings, this research investigates whether and under what circumstances consumers either create new mental categories for hybrid products or integrate them into existing categories. Specifically, we propose that this effect is influenced by the degree of product ambiguity and the availability of a new category label. We find that as ambiguity increases, the probability of new category creation augments, but product evaluation deteriorates. However, we also find that a new category label can reduce the effects of ambiguity and can improve product evaluation. Thus, the results fill the existing gap in research on the cognitive integration of hybrid products and shed light on how managers may position these products successfully.     

国外新产品扩散模型研究的新进展

总结回顾了1990年以后国外新产品扩散模型的主要研究进展,其成果主要体现在2个方面:①在Bass模型基础上的改进扩展模型,主要是引入营销组合变量、供给约束、竞争、补充性产品及产品更新换代的影响,并考虑成倍购买和“试用—再买”的情况;②脱离Bass模型的研究平台,开创全新架构的模型,包括购买力驱动、战略驱动、异质性驱动扩散模型,以及空间扩散和娱乐品扩散模型。比照1990年MAHA JAN等指出的11个未来的研究方向,可见1990年以来新产品扩散的研究取得了很大的进展,在一些方面的发展是突破性的,在另一些方面则严重不足。尤其是近年来新兴技术及其产品的迅猛增长应该成为未来研究关注的一个重点。     

Drivers of private-label purchase behavior across quality tiers and product categories

Private labels hold a substantial share of consumers’ wallets and their popularity is still growing as they spread into various product categories and quality tiers. To determine the right branding strategy, in terms of offering uniform or different private-label brands across product categories, retailers have to know whether consumers use their private-label experience across product categories and private-label tiers. Therefore, we examine different determinants of consumers’ consideration sets. We apply proneness for certain private-label tiers, product categories purchased, purchase frequency, and variety seeking as internal determinants, which contribute to consumers’ knowledge and experience with private labels. Further, we use consumers’ price consciousness and promotion sensitivity as external determinants, which the retailer can use to influence consumers’ consideration sets in the short run. Our analyses are based on large-scale loyalty program data for a period of 24 months. In particular, we use the first 12 months to derive the determinants of consumers’ share of wallets regarding different private-label quality tiers in the second half of the sample. We conduct our analyses for 12 different product categories and aggregate the results by using meta-analytic techniques. Notably, some determinants show dissimilar effects across product categories (e.g., price consciousness and promotion sensitivity), while others (e.g., private-label proneness) are rather similar. We find that consumers’ general proneness for certain private-labels tiers leads to a propensity to purchase them in a specific category and in adjacent quality tiers. Further, we reveal that product category characteristics moderate the determinants of private-label share.     

Integrating Social Network Effects in the Share‐Of‐Choice Problem

Accounting for social network effects in marketing strategies has become an important issue. Taking a step back, we seek to incorporate and analyze social network effects on new product development and then propose a model to engineer product diffusion over a social network. We build upon the share‐of‐choice (SOC) problem, which is a strategic combinatorial optimization problem used commonly as one of the methods to analyze conjoint analysis data by marketers in order to identify a product with largest market share, and show how to incorporate social network effects in the SOC problem. We construct a genetic algorithm to solve this computationally challenging (NP‐Hard) problem and show that ignoring social network effects in the design phase results in a significantly lower market share for a product. In this setting, we introduce the secondary operational problem of determining the least expensive way of influencing individuals and strengthening product diffusion over a social network. This secondary problem is of independent interest, as it addresses contagion models and the issue of intervening in diffusion over a social network, which are of significant interest in marketing and epidemiological settings.     

在线评论与产品介入对虚拟购物车选择决策的影响研究——基于消费者介入理论

了解购物车放弃等"非购买"行为能丰富消费者决策行为理论,帮助电商制定个性化营销策略。消费者介入理论认为,产品介入取决于所耗的信息成本,目前研究对介入度过于定性与模糊。本文基于单品层级细分三种产品介入度：时间介入度,注意力介入度,关注介入度;考虑产品介入的时序依赖效应,在线评论对于购物车放弃的影响。本文以离散选择模型对购物车决策进行建模,结合京东商城点击流数据分析表明（1）时间介入度正向显著地影响购物车放弃和购买行为,但对后者效应更强。（2）对产品的注意力介入度越高,在购物车中放弃的可能性越低;但也会降低购买意愿。（3）产品的关注介入度与消费者放弃购物车行为的存在负向关系。此外,本文结合差评率的交叉弹性仿真,发现（4）高关注介入度的产品更易受差评率影响而放弃购物车;时间介入度和差评率两者正向平稳地影响放弃购物车可能性。本研究为个性化推荐系统和社交电商的在线评论管理实践提供了理论依据。     

Does umbrella branding really work? Investigating cross-category brand loyalty

Numerous studies on the drivers of brand extension success found evidence that parent-brand characteristics and the fit between parent brand and transfer product are the main and most influential factors driving brand extension success. However, the ability of a brand to transfer its brand loyal customers from the parent to the extension category has been widely neglected. Brand loyalty can be regarded as a consequence of the underlying assumption of customers transferring their quality perceptions, their brand knowledge, and their experience with the brand from one category to the other. We find empirical evidence that consumers who are loyal to the brand in the leading (parent) product category show a higher probability to be loyal to that same brand in another (extension) category compared to those consumers who are not loyal in the leading category. Moreover, as the overall success of the extension includes positive retroactive effects of the extension product on the parent product or brand, the arising question is whether there are differences between extension product categories regarding their attachment to the parent category and their ability to stimulate brand loyal purchases in the parent category, i.e., speaking of ‘leader’ and ‘follower’ categories in terms of brand loyal purchase behavior. This might even hold true for the relationship of any two categories the brand competes.     

Demand Functions in Decision Modeling: A Comprehensive Survey and Research Directions

A variety of mathematical forms have been developed to characterize demand functions which depend on a firm's operational and marketing activities. Such demand functions are being increasingly used by researchers in economics and different functional areas of business. We provide a comprehensive survey of commonly used demand models which depend on (i) price, (ii) rebate, (iii) lead time, (iv) space, (v) quality, and (vi) advertising. Our survey includes single firm–demand models in each category, as well as game theoretic multifirm models involving strategic interaction among the firms. We observe that certain types of functional forms, such as linear, power/iso‐elastic, multinomial logit, and multiplicative competitive interaction, have been widely used to construct various demand models in all six categories, but that a large majority of publications deal with categories (i) and (v) of demand models. For each of the six categories, we survey relevant functional forms in the representative papers, and discuss the main properties, the advantages, the disadvantages, and comment on possible future research directions. We also present discussions of the applications of these analytical demand models in empirical studies. The article ends with a summary of our major findings.     

Postdisaster Housing Stages: A Markov Chain Approach to Model Sequences and Duration Based on Social Vulnerability

Housing recovery is an unequal and complex process presumed to occur in four stages: emergency shelter, temporary shelter, temporary housing, and permanent housing. This work questions the four-stage typology and examines how different types of shelter align with multiple housing recovery stages given different levels of social vulnerability. This article also presents a Markov chain model of the postdisaster housing recovery process that focuses on the experience of the household. The model predicts the sequence and timing of a household going through housing recovery, capturing households that end in either permanent housing or a fifth possible stage of failure. The probability of a household transitioning through the stages is computed using a transition probability matrix (TPM). The TPM is assembled using proposed transition probability models that vary with the social vulnerability of the household. Monte Carlo techniques are applied to demonstrate the range of sequences and timing that households experience going through the housing recovery process. A set of computational rules are established for sending a household to the fifth stage, representing a household languishing in unstable housing. This predictive model is exemplified on a virtual community, Centerville, where following a severe earthquake scenario, differences in housing recovery times exceed four years. The Centerville analysis results in nearly 5% of households languishing in unstable housing, thereby failing to reach housing recovery. These findings highlight the disparate trajectories experienced by households with different levels of social vulnerability. Recommendations are provided at the end for more equitable postdisaster recovery policies.     

服务质量影响市场需求下资金约束型网购供应链协调研究

高质量发展服务业已经写入国家战略，其重要性在以顾客需求为导向的网购市场经济中尤为突出。企业服务质量直接决定顾客的购物体验。在供应链意图改善顾客体验但零售商受资金约束的背景下，考虑服务质量对市场需求的影响，设计回购契约与"基于目标销售量的信用契约"组合，构建资金约束型网购供应链协调决策模型，并对其进行求解以获得供应链最优经营策略。研究结果显示，运用最优策略不仅有助于缓解零售商的资金压力，而且能激励其提高服务质量，改善顾客购物体验；所得契约设计不仅能实现网购供应链协调，而且能实现供应链总利润在节点企业之间的任意分配，提高了契约的操作性，保障了最优策略的有效性。