Can customer engagement in social media be used as a predictor of operating revenue in SMEs?

Only a few studies have analyzed the direct or material contributions of customer engagement (CE) on social media. This is the first study that specifically examines the capability CE on social media to predict an indicator of business performance, such us the operating revenue, in a sample of small and medium-sized enterprises (SMEs). The author explores this issue by differentiating between the two main approaches used by SMEs in the management of their social networks (internal management with non-specialized staff and outsourced management with specialized professionals). The study, which uses time series analysis by applying the Autoregressive Integrated Moving Average (ARIMA) modeling technique, examines one hundred SMEs over an eight-year period (between October 2015 and October 2023). The results show that when social networks are managed internally, by non-specialized staff, CE on social media cannot be used as an indicator to forecast the company’s operating revenue. On the contrary, when the management of social networks is outsourced to specialized professionals (and combined with other digital marketing actions such as SEO, SEM, emailing, e-commerce, etc.), CE on social media can be used to predict the company's operating revenue. Consequently, based on the results obtained, the present study reveals that the role of CE on social media, as a driver of operating revenue, depends on the social network management approach adopted by the company on these platforms.

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Publication Details

Journal
Journal of Open Innovation Technology Market and Complexity
Published
2024-09-15
DOI
https://doi.org/10.1016/j.joitmc.2024.100380
Citations
6
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
6.79
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article

Can customer engagement in social media be used as a predictor of operating revenue in SMEs?

Luis Matosas-López
6 citations
Journal of Open Innovation Technology Market and Complexity
Digital Marketing and Social Media
6.79
article

Can customer engagement in social media be used as a predictor of operating revenue in SMEs?

Luis Matosas-López
article en
6 citations

Abstract

Only a few studies have analyzed the direct or material contributions of customer engagement (CE) on social media. This is the first study that specifically examines the capability CE on social media to predict an indicator of business performance, such us the operating revenue, in a sample of small and medium-sized enterprises (SMEs). The author explores this issue by differentiating between the two main approaches used by SMEs in the management of their social networks (internal management with non-specialized staff and outsourced management with specialized professionals). The study, which uses time series analysis by applying the Autoregressive Integrated Moving Average (ARIMA) modeling technique, examines one hundred SMEs over an eight-year period (between October 2015 and October 2023). The results show that when social networks are managed internally, by non-specialized staff, CE on social media cannot be used as an indicator to forecast the company’s operating revenue. On the contrary, when the management of social networks is outsourced to specialized professionals (and combined with other digital marketing actions such as SEO, SEM, emailing, e-commerce, etc.), CE on social media can be used to predict the company's operating revenue. Consequently, based on the results obtained, the present study reveals that the role of CE on social media, as a driver of operating revenue, depends on the social network management approach adopted by the company on these platforms.

Journal of Open Innovation Technology Market and ComplexityVol. 10(4)
Universidad Rey Juan Carlos (ES)
Decent work and economic growth
Openalex Percentile: Top 3%
Digital Marketing and Social Media
6.79
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Can customer engagement in social media be used as a predictor of operating revenue in SMEs? — Luis Matosas-López · Journal of Open Innovation Technology Market and Complexity (2024) | TGRS Research Map | TGRS