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We know exactly what you want the development of a completely individualised conjoint analysis
(2013)
Improving the predictive validity of conjoint analysis has been an important research objective for many years. Whereas the majority of attempts have been different approaches to preference modelling, data collection or product presentation, only a few scholars have tried to improve predictive validity by individualising conjoint designs. This comes as a surprise because many markets have observed an augmented demand for customised products and highly heterogeneous customers' preferences. Against this background, the authors develop a conjoint variant based on a completely individualised conjoint design. More concretely, the new approach not only individualises the attributes, but also the attribute levels. The results of a comprehensive empirical study yield a significantly higher validity than existing standardised-level conjoint approaches. Consequently, they help marketers to gain deeper insights into their customers' preferences.
Vorwort
(2013)
The literature on performance information use explains how public managers deal with mainly quantitative data that are systematically collected and formally reported. This article argues that such a narrow understanding is incomplete, as it excludes all kinds of nonroutine performance information, including verbal, ad hoc, and qualitative feedback. To understand how responsive public managers are to performance feedback, alternative sources of performance information need to be taken into account. A literature review suggests considering two important sources of nonroutine feedback: organizational insiders and relevant external stakeholders. Using survey data from German local government, this article shows that public managers prefer to use nonroutine feedback over routine data from performance reports. Furthermore, a regression analysis indicates that different sources of performance information require different determinants to trigger their use. This finding is essential because it suggests that explanations of performance information use can covary with the information source studied.
The law of targeting
(2013)