Impact of digital transformation on the individual job performance of insurance companies in peru

Carla Victoria Guzmán-Ortiz, Nohelia Gabriela Navarro-Acosta, Wilmer Florez-Garcia, Wagner Vicente-Ramos

Producción científica: Artículo CientíficoArtículo originalrevisión exhaustiva

13 Citas (Scopus)

Resumen

The objective of this study was to analyze and determine the impact of digital transformation on the individual job performance of insurance companies in Peru. The deductive inferential scientific method of explanatory level was used, with a non-experimental design, to four insurance companies that operate in the regions of Arequipa, Cusco, Iquitos, Lima, Tacna and Trujillo. The results generated by structural equations show that customer service experience (CSE), based on digital transformation, had a positive impact on task performance (p <0.05) and contextual performance (p <0.05); in contrast, the customer service experience (CSE), based on digital transformation, was found to have no impact on counterproductive behavior (p> 0.05). In relation to the collaborator's capabilities (CC) based on digital transformation, the results reveal that it had a significant influence on task performance (p <0.05) and contextual performance (p <0.05), while it did not have any impact on counterproductive behavior (p> 0.05). Likewise, processes based on digital transformation (P) significantly influence task performance (p <0.05) and contextual performance (p <0.05), unlike counterproductive behavior that did not present a causal link with the processes (p> 0.05). Finally, the business model based on digital transformation (BM) had no implications for task performance (p> 0.05), contextual performance (p> 0.05) and counterproductive behaviors (p> 0.05). The conclusion of the study indicates that the customer service experience, the collaborator's capabilities and processes based on digital transformation contribute to the performance and contextual performance of the workers of the insurance companies in Peru.

Idioma originalInglés estadounidense
Páginas (desde-hasta)337-346
-10
PublicaciónInternational Journal of Data and Network Science
Volumen4
N.º4
DOI
EstadoIndizado - 2020

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© 2020 by the authors; licensee Growing Science, Canada.

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