
doi: 10.1086/296096
Conjoint analysis (or trade-off analysis) has become increasingly used in marketing. Essentially, the techniques attempt to parse the appeals of a product or concept into a set of factors, assign utility values to the separate levels of each factor, and finally, under the assumption of separability, determine the utility value of any product or concept by adding (or multiplying) the utility values of the individual levels of each of the factors embodied in the product or concept. A good expository description of conjoint analysis is given in Green and Srinivasan (1978). For notational convenience, I present a brief description herein. Formally, if we are considering n factors, with the ith factor (i = 1, . . . , n) having mi levels, then we shall represent a bundle as an n-tuple (i1, i2, . . , ia), where
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 13 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
