Document Type
Article
Abstract
A manufacturer’s assortment is the set of products that the company offers to its customers. Assortment planning considerably affects both the sales revenue and product offering costs for the company and it had experienced growing attention across different industries over recent decades. In this study, we propose a modeling framework that seeks to identify the optimal assortment for a manufacturer of configurable products (in particular, automobiles). Our model accounts for environmental considerations (Corporate Average Fuel Economy requirements, tail-pipe emissions, and greenhouse gas emissions related to the production of the fuel used to power the vehicle) during assortment planning. We formulate the economic and environmental requirements in the model through a mixed-integer programming framework and present a hypothetical product case study motivated by an American automaker that involves 120 potential configurations employing different engine technologies (gasoline, diesel, and hybrid technologies). Notwithstanding consideration for consumer perceptions and acceptance, the results of this research work show that diesel technologies are a better choice to satisfy average fuel economy requirements compared to hybrid and conventional powertrains with current technology maturity.
Disciplines
Management Sciences and Quantitative Methods | Mechanical Engineering | Operations and Supply Chain Management
Recommended Citation
Taghavi, A. & Chinnam, R. B. (2014). Assortment Planning of Automotive Products: Considerations for Economic and Environmental Impacts of Technology Selection. Journal of Cleaner Production, 70(1): 132-144, doi: 10.1016/j.jclepro.2014.02.004
Author's unformatted final accepted manuscript
Included in
Management Sciences and Quantitative Methods Commons, Mechanical Engineering Commons, Operations and Supply Chain Management Commons
Comments
NOTICE IN COMPLIANCE WITH PUBLISHER POLICY: This is the author’s final manuscript version, post-peer-review, of a work accepted for publication in Journal of Cleaner Production. Changes resulting from the publishing process may not be reflected in this document; changes may have been made to this work since it was submitted for publication. This version has been formatted for archiving; a definitive version was subsequently published in Journal of Cleaner Production, 70(1): 132-144 (May 2014) http://dx.doi.org/10.1016/j.jclepro.2014.02.004