Designing Fair and Sustainable Leasing

TL;DR: A planned study using conjoint analysis to determine consumer preferences for fair, sustainable, and data-driven leasing contracts. Wear-based pricing models like the Fair-Wear Pricing Model (FWPM) offer a promising, sustainable alternative to traditional leasing. By linking rates to actual product wear via IoT data, they aim to be fairer and incentivize resource-conscious behavior. However, the optimal design of such contracts from a consumer perspective remains unknown.

This study aims to quantify consumer preferences for the key attributes of a wear-based leasing model. We will employ a choice-based conjoint analysis to understand how consumers trade off critical features like the pricing structure (fixed vs. variable costs), the level of data privacy, the entity handling their data, and the type of sustainability incentives offered.

The research is expected to reveal the relative importance of these features and identify distinct consumer segments based on their preferences for risk, sustainability, and privacy. Furthermore, we plan to estimate consumers’ willingness-to-pay for specific attributes, such as enhanced data privacy through an independent third-party data handler.

Ultimately, the results will provide actionable insights for designing and marketing fair and sustainable leasing contracts that align with consumer preferences, bridging the gap between innovative models and successful market adoption.

Forthcoming.