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Prescribers' opinions to identify competitive groups: a comparative analysis in the pharmaceutical industry.

Authors :
Tejero-Martos, Veronica
Vila, Natalia
Küster, Inés
Source :
Expert Review of Pharmacoeconomics & Outcomes Research; Aug2021, Vol. 21 Issue 4, p753-763, 11p
Publication Year :
2021

Abstract

A firm must identify its key competitors (those that belong to the same competitive group), especially when operating in highly competitive industries, such as drug products. Experts who prescribe products to the final consumer play a crucial role in identifying the key competitors of a firm. In this context, the present paper aimed to determine if significant differences exist between two groups of prescribers (commercial and social) regarding the competitive structure that both groups identify using subjective information obtained through (i) categorization methods and (ii) evaluation methods. A sample of 104 prescribers related to the sale of cosmetic pharmaceuticals was interviewed (53 commercials and 51 social prescribers). Multidimensional scaling was used to obtained perceptual maps that visually represented the competitive space for each group of prescribers. Cluster analysis was employed to identify the competitive structure (competitive clusters) for each group of prescribers. Bilateral Pearson correlations and Mobility Rates were applied to compare the perceptual maps and the identified clusters, respectively. Competitive spaces and structures from both groups of prescribers were partially convergent, regardless the information was collected with categorization methods or evaluation ones. The competitive perceptual map identified by the commercial prescribers converges, to a certain extent, with the competitive perceptual map identified by the social prescribers when categorization data is used (correlation between maps = 0.322; p < 0.01). The same occurs when both targets (commercial prescribers and social prescribers) are compared using evaluation data (correlation between maps = 0.69; p < 0.01). In addition, the mobility rate (MR) shows 31.25% of convergence between the clusters identified on these maps using categorization methods; and 6.25% of convergence when evaluation data are used. There are certain perceptual differences depending on prescribers' occupation, although these differences are not significant. On the contrary, some differences due to the information collecting method (categorization versus evaluation) have been identified. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14737167
Volume :
21
Issue :
4
Database :
Complementary Index
Journal :
Expert Review of Pharmacoeconomics & Outcomes Research
Publication Type :
Academic Journal
Accession number :
152096697
Full Text :
https://doi.org/10.1080/14737167.2020.1803065