Scalable Inference of Customer Similarities from Interactions Data using Dirichlet Processes

Under the sociological theory of homophily, people who are similar to one another are more likely to interact with one another. Marketers often have access to data on interactions among customers from which, with homophily as a guiding principle, inferences could be made about the underlying similarities. However, larger networks face a quadratic explosion in the number of potential interactions that need to be modeled. This scalability problem renders probability models of social interactions computationally infeasible for all but the smallest networks. In this paper we develop a probabilistic framework for modeling customer interactions that is both grounded in the theory of homophily, and is flexible enough to account for random variation in who interacts with whom. In particular, we present a novel Bayesian nonparametric approach, using Dirichlet processes, to moderate the scalability problems that marketing researchers encounter when working with networked data. We find that this framework is a powerful way to draw insights into latent similarities of customers, and we discuss how marketers can apply these insights to segmentation and targeting activities

Anomalies in Estimates of Cross-Price Elasticities for Marketing Mix Models: Theory and Empirical Test

We investigate the theoretical possibility and empirical regularity of two troublesome anomalies that frequently arise when cross-price elasticities are estimated for a set of brands expected to be substitutes. These anomalies are the occurrence of: (a) negatively signed cross-elasticities; and (b) sign asymmetries in pairs of cross price elasticities. Drawing upon the Slutsky equation from neoclassical demand theory, we show how and why these anomalies may occur when cross elasticities are estimated for pairs of brands that are substitutes. We empirically examine these issues in the context of the widely used Multiplicative Competitive Interaction (MCI) and Multinomial Logit (MNL) specifications of the fully extended attraction models (Cooper and Nakanishi 1988). Utilizing a database of store-level scanner data for 25 categories and 127 brands of frequently purchased branded consumer goods, we find that about 18% of a total of 732 cross elasticity estimates are negative and approximately 40% of the 366 pairs of cross elasticities are sign asymmetric. Finally, we find that the occurrence of negatively signed cross elasticities can be partially explained by a set of hypothesized relationships between cross-price elasticities and brand share and elasticities of income and category demand.

Health shocks, coping strategies and foregone healthcare among agricultural households in Kenya

Risks are a central part of life for households in low-income countries and health shocks in particular are associated with poverty. Formal mechanisms protecting households against the financial consequences of shocks are largely absent, especially among poor rural households. Our aim is to identify the relative importance of health shocks and to explore factors associated with coping behaviour and foregone care. We use a cross-sectional survey among 1226 randomly selected agricultural households in Kenya. In our sample, illness and injury shocks dominate all other shocks in prevalence. Almost 2% of households incurred catastrophic health expenditure in the last year. Using a probit model we identified the main coping strategies associated with facing a health shock: (1) use savings, (2) sell assets and (3) ask for gifts or loans. One in five households forewent necessary care in the last 12 months. We conclude that health shocks pose a significant risk to households. Implementing pre-payment or saving mechanisms might help protect households against the financial consequences of ill health. Such mechanisms, however, should take into account the competing shocks that agricultural households face, making it almost impossible to reserve a share of their limited resources for the protection against health shocks only

Effects of a smartphone application on maternal health knowledge and dietary diversity among pregnant women in india:A randomized single center pilot study

Background:India contributes to one-fifth of infant and maternal deaths globally. Healthy lifestyles during pregnancy combined with good quality health care can help to avoid many maternal and neonatal deaths. Access to appropriate information is important for developing or maintaining a healthy lifestyle. The increased coverage of smartphones across low- and middle-income countries (LMICs) has given rise to smartphone apps supporting healthy pregnancies. The objective of this study is to evaluate the effects of the smartphone application Together For Her on maternal health knowledge and dietary diversity among pregnant Indian women. Methods:We ran a randomised single-centre pilot study in a private hospital in Maharashtra, India. We randomly selected pregnant women at $20 weeks of gestation who were invited to download the application, in addition to regular antenatal care. The control group only received regular antenatal care. Knowledge about a healthy lifestyle during pregnancy, self-reported dietary diversity and individual characteristics were collected via telephone interviews at baseline (T0), midline (T0 + 4 weeks) and endline (T0 + 12 weeks). Results:Complete data were collected for 179 respondents (intervention:94; control:85). Respondents in the intervention group showed larger increases in their knowledge over the 12-week study period, with an overall knowledge increase of 13.4 percentage points (P&lt;0.001). The largest effects were found in the modules anaemia, breastfeeding and skin-to-skin contact. Self-reported diversity in nutritional intake also improved significantly more in the intervention group than in the control group. Conclusions:Smartphone applications can effectively supplement antenatal care by increasing women’s knowledge about a healthy lifestyle during pregnancy, which is likely to reduce the risk of adverse maternal health outcomes. Future research includes the roll-out of a larger multi-centre RCT to assess the effect of the smartphone application on health outcomes.</p

Public preferences for policies promoting a healthy diet:a discrete choice experiment

BACKGROUND: Worldwide obesity rates have nearly tripled over the past five decades. So far, policies to promote a healthier diet have been less intrusive than those to reduce tobacco and alcohol consumption. Not much is known about public support for policies that aim to promote a healthy diet. In this study, a discrete choice experiment (DCE) was used to elicit stated preferences for policies varying in intrusiveness among a representative sample of the public of The Netherlands. METHODS: The choice tasks presented respondents a hypothetical scenario of two policy packages, each comprising a mix of seven potential policies that differed in level of intrusiveness. We estimated mixed logit models (MXL) to estimate respondents’ preferences for these policies and performed latent class analyses to identify heterogeneity in preferences. RESULTS: The MXL model showed that positive financial incentives like subsidies for vegetables and fruit yielded most utility. A tax of 50% on sugary drinks was associated with disutility while a tax of 20% was associated with positive utility compared to no tax at all. We identified three subgroups with distinct preferences for the seven policies to promote a healthy diet, which were characterized as being “against”, “mixed” and “pro” policies to promote a healthy diet. CONCLUSION: Preferences for policies promoting a healthy diet vary considerably in the Dutch population, particularly in relation to more intrusive policies. This makes selection and implementation of a policy package that has wide public support challenging. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10198-022-01554-7