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Predicting the Reputation of Pharmaceutical Firms with Financing and Geographical Location Data

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Predicting the Reputation of Pharmaceutical Firms with Financing and Geographical Location Data

dc.contributor.author	Alcaide González, María Ángeles
dc.contributor.author	De la Poza, Elena
dc.contributor.author	Guadalajara Olmeda, Natividad
dc.date.accessioned	2023-10-06T09:31:15Z
dc.date.available	2023-10-07T04:45:06Z
dc.date.issued	2021	es_ES
dc.identifier.citation	Alcaide, M. Á., de la Poza, E., & Guadalajara, M. a. N. (2021). Predicting the reputation of pharmaceutical firms with financing and geographical location data. Mathematics, 9(16).	es_ES
dc.identifier.uri	https://hdl.handle.net/10550/90048
dc.description.abstract	Reputation is a strategic asset for firms, but has been poorly studied in the pharmaceutical industry, particularly in relation to their financial and stock-market performance. This work aimed to predict the probability of a firm being included in a pharmaceutical reputation index (Merco and PatientView), and the position it occupies, according to its economic–financial and stock-market outcomes and its geographical location. Fifty firms with excellent sales in 2019 and their rankings in 2017–2019 were employed. The methodology followed was logistic regression. Their research and development (R&D) expenditures and dividends strongly influenced them being included in both rankings. Non-Asian pharmaceutical companies were more likely to belong to the two reputation indices than Asian ones, and to occupy the best positions in the Merco ranking. Although no large differences appeared in the firms in both indices, differences were found in the position that pharmaceutical companies occupied in rankings and in the variables that contribute to them occupying these positions. Being in PatientView influenced dividends, sales, and income, while appearing in Merco showed accounting aspects like value in books and debt ratio.	es_ES
dc.language.iso	en	es_ES
dc.publisher	MDPI AG	es_ES
dc.subject	economic–financial perspective	es_ES
dc.subject	geographical location	es_ES
dc.subject	listing	es_ES
dc.subject	logistic regression	es_ES
dc.subject	pharmaceutical	es_ES
dc.subject	atientview	es_ES
dc.subject	merco	es_ES
dc.title	Predicting the Reputation of Pharmaceutical Firms with Financing and Geographical Location Data	es_ES
dc.type	journal article	es_ES
dc.subject.unesco	UNESCO::CIENCIAS ECONÓMICAS	es_ES
dc.identifier.doi	10.3390/math9161893	es_ES
dc.accrualmethod	S	es_ES
dc.embargo.terms	0 days	es_ES
dc.type.hasVersion	VoR	es_ES
dc.rights.accessRights	open access	es_ES