Cross-Category Retailing Management: Substitution and Complementarity

Problem definition: This paper studies pricing and assortment management for cross-category products, a common practice in brick-and-mortar retailing and e-tailing. Academic/practical relevance: We investigate the complementarity effects between the main products and the secondary products, in addition to the substitution effects for products in the same category. Methodology: In this paper, we develop a multistage sequential choice model, under which a consumer first chooses a main product and then selects a secondary product. The new model can alleviate the restriction of the independence of irrelevant alternatives property and allows more flexible substitution patterns and also takes into account complementarity effects. Results: We characterize the impact of the magnitude of complementarity effects on pricing and assortment management. For the problems that are hard to solve optimally, we propose simple heuristics and establish performance guarantee. In addition, we develop easy-to-implement estimation algorithms to calibrate the proposed sequential choice model by using sales data. Managerial implications: We show that ignoring or mis-specifying complementarity effects may lead to substantial losses. The methodologies on modeling, optimization, and estimation have potential to make an impact on cross-category retailing management.

The Threshold-Crossing Effect: Just-Below Pricing Discourages Consumers to Upgrade

Managers often set prices just-below a round number (e.g., $39) – a strategy that lowers price perceptions and increases sales. The authors question this conventional wisdom in a common consumer context: upgrade decisions (e.g., whether to upgrade a car or hotel room). Seven studies—including one field study—provide empirical evidence for a threshold-crossing effect. When a base product is priced at or just-above a threshold, consumers are more likely to upgrade and spend more money (studies 1–3) because they perceive the upgrade option as less expensive (study 4), and they place less weight on price (study 5). Testing theoretically motivated and managerially relevant boundary conditions, studies find that the threshold-crossing effect is mitigated under sequential choice (study 6) and when an upgrade price crosses an upper threshold (study 7). These studies demonstrate that a small increase in price on a base product can decrease price perceptions of an upgrade option and, thus, increase consumers’ likelihood to upgrade. It suggests that just-below pricing, while sometimes advantageous at first, may not always be an optimal strategy for managers trying to encourage consumers to ultimately choose an upgrade option.

Cingulate-motor circuits update rule representations for sequential choice decisions

Anterior cingulate cortex mediates the flexible updating of an animal's choice responses upon rule changes in the environment. However, how anterior cingulate cortex entrains motor cortex to reorganize rule representations and generate required motor outputs remains unclear. Here, we demonstrate that chemogenetic silencing of the projection terminals of cingulate cortical neurons in secondary motor cortex disrupted sequential choice performance in trials immediately following rule switches, suggesting that these inputs are necessary to update rule representations for choice decisions stored in the motor cortex. Indeed, the silencing of cingulate cortex decreased rule selectivity of secondary motor cortical neurons. Furthermore, optogenetic silencing of cingulate cortical neurons that was temporally targeted to error trials immediately after rule switches exacerbated errors in following trials. These results suggest that cingulate cortex monitors behavioral errors and update rule representations in motor cortex, revealing a critical role for cingulate-motor circuits in adaptive choice behaviors.

Framing as a Mechanism for Self-Control

This chapter approaches self-control via a problem arising in decision theoretic discussions of sequential choice within a broadly Humean conception of action and motivation. How can agents stick to their plans and honor their commitments in the face of temptation, if at the moment of choice the short-term temptation motivationally outweighs the long-term goal? After introducing the sequential choice puzzle in section 19.1, section 19.2 surveys suggestive psychological work on the mechanisms of self-control, pointing to the importance of how outcomes are framed. Section 19.3 offers a solution to the sequential choice problem in terms of frame-sensitive reasoning—i.e. reasoning that allows outcomes to be valued differently depending on how they are framed, even when the agent knows that she is dealing with two (or more) different ways of framing the same outcome. Section 19.4 argues that this type of quasi-cyclical, frame-sensitive reasoning can indeed be rational.

The Moderating Effect of Buying Impulsivity on the Dynamics of Unplanned Purchasing Motivations

Previous studies of in-store decision making have assumed that motivations for unplanned purchases are homogeneous throughout a shopping trip. In response to this assumption, the authors develop a conceptual framework to explain how consumers’ internal (i.e., intrinsic) and external (i.e., extrinsic) motivations for unplanned purchases actually vary during a shopping trip. Two field studies and five online experiments provide evidence that the personality trait of buying impulsivity predicts differences in whether a shopper initially focuses on internal motivations (e.g., “because I love it”) or external motivations (e.g., “because it is on sale”) for unplanned purchases at the beginning of a shopping trip and, consistent with a mechanism of motivation balancing, that motivations for unplanned purchases change as a shopper satisfies their initial motivations. The studies also demonstrate how the level of buying impulsivity influences the effectiveness of point-of-purchase messages at stimulating unplanned purchases and consumers’ relative spending on unplanned purchases. Overall, these findings address conflicting results in previous shopping studies, advance the literature streams on consumer motivation and sequential choice, and contribute insights to enhance shopper-marketing programs.

Agent-Relative Prerogatives and Suboptimal Beneficence

The first part of Chapter 11 uses considerations of sequential choice to argue that suboptimal beneficence is impermissible. The second part shows how the prohibition on suboptimal beneficence follows from an agent-relative theory that understands permissible actions in terms of a dominance principle defined over both the agent-relative and the agent-neutral ordering. This theory incorporates agent-relative prerogatives that ensure that agents are not required to do what is impartially best, yet rules out suboptimal beneficence. The third part shows that the prohibition on suboptimal beneficence is in tension with dynamic consistency, since it leads to violations of expansion consistency condition BETA. If an agent makes use of myopic choice principles (which are purely forward-looking) or sophisticated choice principles (that make use of backwards induction), then there can be cases in which he can, by means of a sequence of permissible choices, bring about an outcome that is deemed to be impermissible from the outset. This problem is addressed by developing global choice principles that ensure dynamic consistency.

Dynamic Learning of Sequential Choice Bandit Problem under Marketing Fatigue

Motivated by the observation that overexposure to unwanted marketing activities leads to customer dissatisfaction, we consider a setting where a platform offers a sequence of messages to its users and is penalized when users abandon the platform due to marketing fatigue. We propose a novel sequential choice model to capture multiple interactions taking place between the platform and its user: Upon receiving a message, a user decides on one of the three actions: accept the message, skip and receive the next message, or abandon the platform. Based on user feedback, the platform dynamically learns users’ abandonment distribution and their valuations of messages to determine the length of the sequence and the order of the messages, while maximizing the cumulative payoff over a horizon of length T. We refer to this online learning task as the sequential choice bandit problem. For the offline combinatorial optimization problem, we show a polynomialtime algorithm. For the online problem, we propose an algorithm that balances exploration and exploitation, and characterize its regret bound. Lastly, we demonstrate how to extend the model with user contexts to incorporate personalization.