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Original Research

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

, ORCID Icon & ORCID Icon
Pages 753-763 | Received 01 Jun 2020, Accepted 27 Jul 2020, Published online: 24 Sep 2020
 

ABSTRACT

Background

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.

Method

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.

Result

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.

Conclusions

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.

Statement of contribution

Only few studies have studied the competitive structure of an industry by comparing perceptions of different groups of key experts; and even less comparing different information collecting methods. This work compares if the competitive structure identified by commercial prescribers (those who sell the product), differ (or not) to what social prescribers (opinion leaders) think; both, when categorization and evaluation methods are used. Such differential results are particularly useful in designing communication strategies aimed at both prescribers.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewers disclosure

Peer reviewers on this manuscript have no relevant financial relationships or otherwise to disclose.

Author contribution statement

All the authors have contributed in the different parts of the paper

Additional information

Funding

This paper was not funded.

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