作者: BP Bart Knijnenburg , MC Martijn Willemsen , R Ron Broeders
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摘要: People can adopt many different energy-saving measures, but how they be encouraged to take action? Recommender systems could offer a solution, recommender are used and perceived will depend on the level of knowledge people have regarding measures. We test an system that uses Multi-Attribute Utility Theory (MAUT) recommend measures its users. Across four experiments we nine preference elicitation methods for this system, demonstrate users' satisfaction with each these interfaces depends whether expert or novice. Moreover, show is driver behavioral outcomes. In effect, suitable method not only makes users more satisfied system; it also entices them choose higher average savings, their choices as well.