Online consumers are known to be impatient. It is therefore critical for merchant websites to offer relevant recommendations quickly and with minimal customer input to their online visitors. Recommending pertinent items to first-time visitors, however, is particularly challenging. In this paper, we show how conjoint analysis can be leveraged to design a recommender system that elicits customers...

Purpose: Description of the project ProSeBiCA, carried out in order to adapt the marketing research tool Conjoint Analysis for the development of future library services. The paper describes the methodical approach, and provides an overview of the results gained by several user surveys. Design/methodology/approach: The methodical approach includes the use of Adaptive Conjoint Analysis (ACA) and...

Survey experiments are a core tool for causal inference. Yet, the design of classical survey experiments prevents them from identifying which components of a multidimensional treatment are influential. Here, we show how conjoint analysis, an experimental design yet to be widely applied in political science, enables researchers to estimate the causal effects of multiple treatment components and ...

Survey experiments are a core tool for causal inference. Yet, the design of classical survey experiments prevents them from identifying which components of a multidimensional treatment are influential. Here, we show how conjoint analysis, an experimental design yet to be widely applied in political science, enables researchers to estimate the causal effects of multiple treatment components and ...

Conjoint analysis is family of techniques that originated in psychology and later became popular in market research. The main objective of conjoint analysis is to measure an individual’s or a population’s preferences on a class options that can be described by parameters and their levels. We consider preference data obtained in choice based conjoint analysis studies, where one observes test per...

Nowadays, the lead user method [von Hippel, Manag Sci 32(7):791– 805, 1986; Lüthje et al. (Res Pol 34(6):951–965, 2005)] and conjoint analysis [Green and Rao (J Market Res 8(3):355–363, 1971), Baier and Brusch (Conjointanalyse: Methoden Anwendungen Praxisbeispiele, Springer, Heidelberg, 2009)] are widely used methods for (new) product design. Both methods collect and analyze customers’ preferen...

Active learning refers to the mechanism of querying users to accomplish a classification task in machine learning or a conjoint analysis in econometrics with minimum cost. Classification and conjoint analysis have been introduced to design research to automate design feasibility checking and to construct marketing demand models, respectively. In this paper, we review active learning algorithms ...

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