Companies use social media to foster ongoing relationships with customers. One specific way companies do this is by fostering brand communities through fan pages on social networking sites. These virtual platforms allow consumers to become brand advocates. It also allows brands to generate and increase direct engagement with consumers, which is a key metric to assess brand performance. However, little is known about how different post criteria influences distinct levels of social media engagement. To explore this further, we developed a model to analyze the impact of 31 structural, semantic, and morphological content factors over consumer engagement, measured by the number of likes and comments on 680 brand posts from 14 Instagram fan pages across ten sectors. The results revealed a solid model, with an explanatory power of 73.1% (R2) for likes and 47.5% (R2) for comments. The results also established how content factors influenced different engagement levels; i.e. videos with sound, carousel posts with multiple photos, and posts with hashtags achieved higher engagement levels in terms of likes. Contrarily, graphics, interactive content that involved voting, contests, and questions reached higher engagement with regard to comments. We contribute to academic and practical research this new model to study and implement social media solutions that improve customer engagement as part of an organizations’ marketing and branding strategies. The limitations of this paper relate to the size of the sample and the scope of the reviewed literature.

The assessment of teaching quality in blended learning modalities has become a key element in the context of higher education. However, current evaluation systems present certain limitations. Behavioral scales overcome many of these limitations, offering an alternative for this task. This study describes the process of constructing an assessment instrument with behavioral scales to evaluate university teachers in blended learning modalities, following the BARS (Behavioral Anchored Rating Scales) methodology. The design process included interviews and surveys involving a total of 477 students, as well as a panel of professors who were experts in this teaching modality. The behavioral scales in the final instrument highlight the importance of certain particularly significant teaching-related aspects of blended learning models, namely: teacher-student communication; learning resources; course design; and the teacher’s technical competencies. The authors conclude that the final instrument provides clear and unambiguous feedback, enables the teacher to take specific corrective measures, and reinforces the formative purpose of evaluation in these modalities.

The present study aims to provide an overview of the digital marketing strategies in social network services (SNSs) used in America and Europe. This work, unlike previous research that analyze digital marketing strategies in SNSs in a single geographic area, presents as the main contribution and value the use of a comparative approach between continents; specifically, then, an approach that allows comparing the management strategies used in these two areas. The research takes a sample of forty organizations, twenty American and twenty European. The author applies a descriptive examination followed by a parametric analysis using the t-test procedure over a total of 158,208 publications on Twitter. The findings show significant differences in the management approaches applied in these two continents. Even though the digital marketing strategies in SNSs should be based on dialogue and interaction with the organization’s target audience, this point can be more or less important, depending on the continent. While European organizations confer great importance to the interaction with its audience, American organizations tolerate a greater degree of one-way communication. The author concludes that the paradigms governing the definition of digital marketing strategies in SNSs at the global level, a priori thought to be universal, probably require reformulation if they are to be well adapted to the specific geographic areas where these strategies are implemented.

The objective of this research is to identify to what extent volumes, components, time slots, and publication topics improve customer engagement with Spanish automotive brands through social networks. The study considers thirteen brands and the total number of publications created by them in 2020 (23,670 publications) on the social network Twitter. Applying machine learning algorithms followed by multiple linear regression techniques, the authors examine how the variables previously mentioned affect a customer engagement indicator developed for this purpose. The results reveal that while publication components (links, mentions, and hashtags) and the publication time slot do not affect customer engagement, the volume of retweets made by the brand and publications on customer experience topics (without a direct commercial purpose) significantly improve the customer engagement indicator. The authors conclude that customer engagement in social networks can only be improved by conducting exhaustive analyses of activity data for these platforms. However, such analyses must not be done via generic multisector analyses, which only generate superficial and inapplicable knowledge, but rather through detailed studies for each sector.

Se analizan 106 estudios científicos, extraídos de Web of Science (WoS), sobre la estrategia de contenidos de marca en los medios sociales con el propósito de examinar el estado, la evolución y los diseños metodológicos del ámbito. Para ello se realiza un análisis bibliométrico cuantitativo y descriptivo. Los principales hallazgos son los indicios de madurez científica, como demuestran el predominio de estudios empíricos, la diversidad de actores, unidades de análisis y métodos de investigación, que facilitan nuevas vías de investigación en el área de la comunicación organizacional en entornos digitales.