Design, Adaptation, and Validation of a Digital Marketing Instrument in SMEs
Measuring digital marketing will help evaluate the impact of strategies, increased sales, customer acquisition, and customer retention. This research aims to design, adapt, and validate a scale measuring Digital Marketing in Small and Medium Enterprises. Results were structured as follows: To start,...
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| Autores principales: | , , , |
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| Formato: | Artículo |
| Lenguaje: | inglés |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | Descargar el archivo Enlace permanente (DOI o Handle) Enlace permanente (DOI o Handle) |
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| Sumario: | Measuring digital marketing will help evaluate the impact of strategies, increased sales, customer acquisition, and customer retention. This research aims to design, adapt, and validate a scale measuring Digital Marketing in Small and Medium Enterprises. Results were structured as follows: To start, a thorough literature review was carried out. Subsequently, a panel of 6 marketing experts was made, who evaluated the content. Additionally, data collection was carried out with 711 collaborators from the strategic area of SMEs. As well as, exploratory and confirmatory factor analysis was carried out, obtaining a KMO of 0.95, with a variance of 85.80% in three factors, with factor weights greater than 0.5. The values of the goodness-of-fit index are as follows: residual root mean square (RMS) =0.047; goodness-of-fit index (GFI) = 0.876; adjusted goodness-of-fit index (AGPI) =0.825; comparative fit index (CFI) =0.956; Tucker-Lewis index (TLI) =0.945; normalized fit index (NFI) = 0.945; incremental fit index (IFI) = 0.950 and root mean square residual (RMSEA) =0.072. These values imply an acceptable fit for which the model is adequate, and the scale is valid. Received: 3 March 2024 / Accepted: 22 August 2024 / Published: 05 September 2024 |
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