Methodological approaches to the analysis and assessment of marketing competitive advantages of pharmacy networks

Mala, Zh. V.; Posylkina, O. V.; Nessonova, Maryna

doi:10.24959/sphhcj.17.67

Cited by 1 publication

(2 citation statements)

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“…Since the study involved experts from the PC, which differ significantly in size, turnover, it was necessary to obtain a distribution of the entire sample by cluster based on the values of 13 input variablesassessments of competitiveness strengths to investigate differences in priorities of PC competitiveness. Because of calculations, three PC clusters were identified depending on the priorities of the factors influencing their competitiveness: small PCs form the first cluster; the second clusterform a medium-sized PC; the third clustermost pharmacies, which belong to the large and mega-PC [1]. Indicators that show a significant difference between clusters are highlighted.…”

Section: Research Resultsmentioning

confidence: 99%

“…Various aspects of the implementation of strategic management in the activities of pharmacies and, in particular, PC have been studied in the works of many domestic and foreign scientists. Thus, the publication [1] explores methodological approaches to the analysis and evaluation of marketing competitive advantages of PC; procedure for supporting the development of medical devices: a standard model of the product design process are presented in the publication [2]; in the publication [3] the pharmacy as an environment of pharmaceutical service is estimated. Publications [4,5] investigate strategies and models of distribution of pharmaceutical supplies.…”

Section: Introductionmentioning

confidence: 99%

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Scientific and methodological approaches to modeling the optimal strategy for increasing the competitiveness of pharmacy chains of different sizes

Bondarieva

Malyi

Posylkina

et al. 2021

SR: PS

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The aim of the work is to develop scientific and methodological approaches to modelling the optimal strategy to increase the competitiveness of pharmacy chains (PC), which belong to different clusters. Materials and methods. The algorithm for determining the optimal strategy for increasing the competitiveness of PC for different clusters using the method of constructing a decision tree and cluster analysis is proposed. To solve this problem, an expert survey of more than 400 pharmacy managers, who were part of the PC of different sizes, was previously conducted. According to the results of an expert survey using hierarchical clustering methods based on the values of 13 input variables - scores of the strengths of the competitiveness of the PC, three clusters of networks were identified, each of which proposed its own algorithm for modelling the optimal strategy of competitiveness. Results. Using modern economic and mathematical tools, the distribution of PC depending on their size into clusters for modelling the dynamics of competitiveness is substantiated. Indicators are identified, which show a significant difference between clusters, which was taken into account in the process of modelling and selection of the optimal strategy to increase the competitiveness of PC. It is established that the biggest negative impact on the strategy of increasing the competitiveness of small networks has a slow response to changes in market conditions, the biggest positive impact – the availability of additional services in the networks; for medium PC the most important factors influencing the level of competitiveness are the location of pharmacies and competent management; for large PC – the use of modern automated management programs, the level of efficiency of the marketing complex and location features. The algorithm of the generalized model of “decision tree” for a choice of optimum strategy of increase of competitiveness depending on the size of PC is constructed. It was found that the following factors are of the greatest importance: the size of the PC, the use of the discount card system, and the least - the speed of response to market changes and the stability of the financial condition. Conclusions. The proposed generalized mathematical model of the “decision tree” allows a reasonable approach to choosing the optimal strategy to increase the competitiveness of PC depending on its size. The assessment of the importance of predictor variables for each cluster of PC allows determining the priority factors in the implementation of measures aimed at implementing the chosen strategy to increase competitiveness

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Section: Research Resultsmentioning

confidence: 99%