Needs-based analysis of online customer reviews
Proceedings of the ninth international conference on Electronic commerce
International Journal of Electronic Commerce
Influences of customer preference development on the effectiveness of recommendation strategies
Electronic Commerce Research and Applications
Proceedings of the third ACM conference on Recommender systems
The “I Designed It Myself” Effect in Mass Customization
Management Science
Preference analysis and default optimization in web-based product configuration systems
Journal of Theoretical and Applied Electronic Commerce Research
Product Customization and Customer Service Costs: An Empirical Analysis
Manufacturing & Service Operations Management
Each to his own: how different users call for different interaction methods in recommender systems
Proceedings of the fifth ACM conference on Recommender systems
Journal of Management Information Systems
Do customization programs of e-commerce companies lead to better relationship with consumers?
Electronic Commerce Research and Applications
A study of customization for online business
HCI'13 Proceedings of the 15th international conference on Human Interface and the Management of Information: information and interaction for learning, culture, collaboration and business - Volume Part III
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User design offers tantalizing potential benefits to manufacturers and consumers, including a closer match of products to user preferences, which should result in a higher willingness to pay for goods and services. There are two fundamental approaches that can be taken to user design: parameter-based systems and needs-based systems. With parameter-based systems, users directly specify the values of design parameters of the product. With needs-based systems, users specify the relative importance of their needs, and an optimization algorithm recommends the combination of design parameters that is likely to maximize user utility. Through an experiment in the domain of consumer laptop computers, we show that for parameter-based systems, outcomes, including measures for comfort and fit, increase with the expertise of the user. We also show that for novices, the needs-based interface results in better outcomes than the parameter-based interface.