Navid Mojir Publications

The paper develops the first structural model of organizational buying to study innovation diffusion in a B2B market. Our model is particularly applicable for routinized exchange relationships, whereby centralized buyers periodically evaluate and choose contracts, then downstream users or- der items on contracted terms. The model captures different utility tradeoffs for users and buyers while accounting for how buyer and user choices interact to impact user adoption/usage and buyer contracting. Further, the paper considers the dynamics induced by share of wallet (SOW) pricing contracts, commonly used in B2B markets to reward customer loyalty with discounts for buying more than a threshold share from a supplier. We assemble novel panel data on surgeon usage, SOW contracts, contract switching, and hospital characteristics. We find two segments of hospitals in terms of the relative power of surgeons and buyers: a buyer-centric and a surgeon-centric segment. Further, innovations diffuse faster in teaching hospitals and when surgeries are concentrated among a few surgeons. Finally, we answer such questions as: Should the marketer focus on push (buyer-focused) or pull (user-focused) strategies? Do SOW contracts hurt the innovations of smaller firms? Surprisingly, we find that the contracts can help speed the diffusion of major innovations from smaller players.

In response to price dispersion across stores and price promotions over time, consumers search across both stores (spatial) and time (temporal), in many retail settings. Yet there is no search model in extant research that jointly endogenizes search in both dimensions. We develop a model of spatiotemporal search that nests a finite horizon model of spatial search across stores within an infinite horizon model of inter-temporal search. The model is estimated using an iterative procedure that formulates it as a mathematical program with equilibrium constraints (MPEC) embedded within an E-M algorithm to allow estimation of latent class heterogeneity. The empirical analysis uses data on household store visits and purchases in the milk category. In contrast to extant research, we find that omitting the temporal dimension underestimates price elasticity. We attribute this difference to the relative frequency of household stock outs and purchase frequency in the milk category. Further, contrary to the conventional wisdom that promotions increase store switching and reduces store loyalty, we find that in the presence of search frictions, price promotions can be a store loyalty-enhancing tool.

In retail settings with price promotions, consumers often search across stores and time. However the search literature typically only models one pass search across stores, ignoring revisits to stores; the choice literature using scanner data has modeled search across time, but not search across stores in the same model. We develop a multi-pass search model that jointly endogenizes search in both dimensions; our model nests a nite horizon model of search across stores within an in nite horizon model of inter-temporal search. We apply our model to milk purchases at grocery stores; hence the model also accounts for repeat purchases across time, inventory holding by households and grocery basket effects. We note that the special case without these additional features can be used to study one time purchases with repeat store visits as in the case of durable goods and online shopping. We formulate the empirical model as a mathematical program with equilibrium constraints (MPEC) and estimate it allowing for latent class heterogeneity using an iterative E-M algorithm. In contrast to extant research, we nd that omitting the temporal dimension underestimates price elasticity. We attribute this difference to the relative frequency of household stockouts and purchase frequency in the milk category. Interestingly, increasing the promotional frequency (while reducing its depth to maintain the mean and variance of prices across all stores) can increase loyalty to the household’s preferred store.

In response to price dispersion across stores and price promotions over time, consumers search across both stores and time, in many retail settings. Yet there is no search model in extant research that jointly endogenizes search in both dimensions. We develop a model of search across stores and across time that nests a nite horizon model of search across stores within an in nite horizon model of inter-temporal search. The model is estimated using an iterative procedure that formulates it as a mathematical program with equilibrium constraints (MPEC) embedded within an E-M algorithm to allow estimation of latent class heterogeneity. The empirical analysis uses data on household store visits and purchases in the milk category. In contrast to extant research, we nd that omitting the temporal dimension underestimates price elasticity. We attribute this difference to the relative frequency of household stockouts and purchase frequency in the milk category. Interestingly, we nd that for a given mean and variance in price, increasing the frequency while reducing depth of price promotions across all stores can increase share of visits and pro ts for consumers’ preferred store for the segment with high price sensitivity and low cross-store search cost; consumers who are most prone to search across stores and across time.