Choice Modeling of Laundry Detergent Data for Sustainable Consumption

Marina Kholod, Nikita Mokrenko, Alberto Celani () and Valentina Puglisi
Additional contact information
Marina Kholod: AI, Neurotechnology and Business Analytics Laboratory, Plekhanov Russian University of Economics, Stremyanny Lane, 36, Moscow 117997, Russia
Nikita Mokrenko: AI, Neurotechnology and Business Analytics Laboratory, Plekhanov Russian University of Economics, Stremyanny Lane, 36, Moscow 117997, Russia
Alberto Celani: ABC Department Politecnico di Milano, Polytechnic University of Milan, Leonardo da Vinci Square, 32, 20133 Milan, Italy
Valentina Puglisi: ABC Department Politecnico di Milano, Polytechnic University of Milan, Leonardo da Vinci Square, 32, 20133 Milan, Italy

Sustainability, 2023, vol. 15, issue 24, 1-16

Abstract: Consumer choice modeling takes center stage as we delve into understanding how personal preferences of decision makers (customers) for products influence demand at the level of the individual. The contemporary choice theory is built upon the characteristics of the decision maker, alternatives available for the choice of the decision maker, the attributes of the available alternatives and decision rules that the decision maker uses to make a choice. The choice set in our research is represented by six major brands (products) of laundry detergents in the Japanese market. We use the panel data of the purchases of 98 households to which we apply the hierarchical probit model, facilitated by a Markov Chain Monte Carlo simulation (MCMC) in order to evaluate the brand values of six brands. The applied model also allows us to evaluate the tangible and intangible brand values. These evaluated metrics help us to assess the brands based on their tangible and intangible characteristics. Moreover, consumer choice modeling also provides a framework for assessing the environmental performance of laundry detergent brands as the model uses the information on components (physical attributes) of laundry detergents. Through a comprehensive evaluation of product performance, including brand tangible estimation, we shed light on the sustainability attributes of laundry detergents, offering a roadmap for consumers and manufacturers alike to make more informed, environmentally responsible choices of laundry detergents based on their physical attributes. Knowing the estimates of the attributes for the laundry detergent products, manufacturers can modify their physical attributes, e.g., decrease the amount of the detergent needed for one wash while increasing the total weight of the laundry powder in the package. In this way, more ecology- and consumer-friendly decisions can be made by manufacturers of laundry detergents.

Keywords: brand (product) value; discrete choice models; probit model; hierarchical Bayes; “engineering” coefficients (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/24/16949/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/24/16949/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:24:p:16949-:d:1302552

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().