No abstract

The behavioral literature provides ample evidence that consumer preferences are partly driven by the context provided by the set of alternatives. Three important context effects are the compromise, attraction, and similarity effects. Because these context effects affect choices in a systematic and predictable way, it should be possible to incorporate them in a choice model. However, the literature does not offer such a choice model. This study fills this gap by proposing a discrete-choice model that decomposes a product's utility into a context-free partworth utility and a context-dependent component capturing all three context effects. Model estimation results on choice-based conjoint data involving digital cameras provide convincing statistical evidence for context effects. The estimated context effects are consistent with the predictions from the behavioral literature, and accounting for context effects leads to better predictions both in and out of sample. To illustrate the benefit from incorporating context effects in a choice model, the authors discuss how firms could utilize the context sensitivity of consumers to design more profitable product lines.

Retailers face the problem of finding the assortment that maximizes category profit. This is a challenging task because the number of potential assortments is very large when there are many stock-keeping units (SKUs) to choose from. Moreover, SKU sales can be cannibalized by other SKUs in the assortment, and the more similar SKUs are, the more this happens. This paper develops an implementable and scalable assortment optimization method that allows for theory-based substitution patterns and optimizes real-life, large-scale assortments at the store level. We achieve this by adopting an attribute-based approach to capture preferences, substitution patterns, and cross-marketing mix effects. To solve the optimization problem, we propose new very large neighborhood search heuristics. We apply our methodology to store-level scanner data on liquid laundry detergent. The optimal assortments are expected to enhance retailer profit considerably (37.3%), and this profit increases even more (to 43.7%) when SKU prices are optimized simultaneously.

Social media has moved beyond personal friendships to professional interactions in highknowledge industries. In particular, online discussion forums are sponsored by firms aiming to position themselves as thought-leaders, to gain more insight in their customer base and to generate sales leads. However, while firms can seed discussion by posts, they depend on the forum members to continue the discussion in the form of reactions to these posts. The goal of the current study is to investigate what features and characteristics drive the number of comments that a post receives on an online discussion forum. The empirical setting involves a global manufacturer connecting with health care professionals through a LinkedIn discussion forum. We project that (i) content characteristics, (ii) post characteristics, (iii) author characteristics, and (iv) timing characteristics jointly determine the number of comments a post receives. We show that the readability of the post, the controversiality of the content and the status of the post author have the highest elasticity on the number of comments. These results provide valuable insights for firms on how to build and maintain an attractive online forum through ongoing discussions.