“A Redefinition of the Paradox of Choice”, a paper co-authored by Michal Piasecki and Sean Hanna, was accepted for the Design Computing Cognition conference 2010 (DCC’10).

In the paper builds upon Barry Schwart’z definition of the paradox of choice. The abstract outlines our proposition of reconsideration of the paradox and positions the Breeding Objects Experiment 1 in this context:

Abstract: Barry Schwartz defined the paradox of choice as the fact that in western developed societies a large amount of choice is commonly associated with welfare and freedom but too much choice causes the feeling of less happiness, less satisfaction and can even lead to paralysis. The paradox of choice has been recognized as one of the major sources of mass confusion in context of the B2C online mass customization. We propose to redefine the paradox of choice with an emphasis on the meaning of choice in conjunction with the amount of available options, rather than just the quantity of choice. We propose that it is the lack of meaningful choice, rather than an overwhelming amount of choice, that can cause customers’ feelings of decreased happiness, decreased satisfaction and paralysis. We further propose that since users themselves are often not able to explicitly define what constitutes a meaningful choice, the task they face belongs to the category of ill-defined problems. The challenge for mass customization practitioners is thus not to limit the scope of choice, as has been suggested in previous literature, but to provide users with choice that is relevant to them.

We further discuss two computational approaches to solving problems related to the redefined paradox of choice in the context of the B2C mass customization. The first is based on recommender systems and the second is an implementation of artificial selection in genetic algorithms. We present findings of an empirical comparison of genetic algorithm and parametric product configurators. We find that the genetic algorithm tools, which allow users to move through a solution space by recognition of meaningful options rather than their definition, appear to be more popular among the users when it comes to browsing through solution spaces with larger number of dimensions.

Michal Piasecki attended Mass Customization and Personalization conference in Helsinki (MCPC 2009), where he presented the Review of B2C Online Product Configurators. There where couple of really interesting issues raised during these intensive two days and I would like to begin with discussion of the term “personalization”. Posts on automation in architecture as well as B2C product configurators will follow.

Personalization as an umbrella term

Diversity of meanings applied to the term “personalization” was quite astonishing. For example: Bruce Kasanoff used it to name nearly any kind of mass customization. His examples ranged from products up till body customization with electronic devices.

Personalization as an process in which user is passive with respect to product attributes

Sunnika and Brage’s literature review provided an interesting insight on the distinction between “mass customization” and “personalization”. Their work is an automated literature review, facilitated by text mining algorithms. They have found that “mass customization” referees more often to tangibles, while “personalization” is rather used in the context of “intangibles”. In other words mass customization is likely to be about products, while personalization is associated with information.

This goes in the same line with what Sean Hanna and I proposed in our review. We considered “mass customization” as the process in which user is active with respect to product attributes, while we referred to “personalization” as a process in which user is passive with respect to product attributes. We discussed recommender systems the examples of personalization.

Another interesting input from Sunnika and Brage is that exactly the same distinction in computer science literature was described as a difference between “adaptability” and “adaptivity”. Where “adaptability” is a process in which the user is active, while adaptivity is an automated process.