| dc.description.abstract | The development of dynamic capabilities is crucial for the survival of companies that operate in the contemporary organizational environment, which has been characterized as turbulent (dynamic). In this environment, where more and more social relations are taking place digitally, many organizations have been using social media in their most diverse routines. Given the diffusion of the internet and the use of these digital tools, this study aims to propound and test a theoretical model that measures the importance of social media and dynamic capabilities to improve innovation performance. This model analyzed three dynamic capabilities: internal collaboration capacity, absorptive capacity, and organizational agility. These capabilities were defined through a literature review. The study focused on startups, that is, innovative companies with scalability potential. The startups analyzed are Brazilian and operate in the agribusiness sector. Therefore, this study analyzed AgTech. The focus on this type of organization was because they are companies that operate in environments with a high level of environmental uncertainty, where low levels of innovation performance can negatively affect the development of competitive advantage and, in more critical cases, lead to bankruptcy. The region chosen for the study was Brazil due to the importance of agribusiness in that country's economy and given the Brazilian relevance in the production and export of food. The study is quantitative in nature, and data were collected through questionnaires sent online. Respondents are people who occupy management positions in AgTech, including CEOs, directors, and managers in general. Each AgTech analyzed was represented by a single respondent. Given this, the sample of this study refers to 237 AgTech. Descriptive statistics measures were used to measure the characterization of the sample. Among the results, the most used social media are WhatsApp, Instagram, LinkedIn, and Google Meetings. To test the proposed theoretical model, structural equation modeling with partial least squares estimation (PLS-SEM) was used. The model developed and analyzed consists of six hypotheses and comprises four first-order constructs: social media, absorptive capacity, organizational agility, and innovation performance. The model also presents a second-order construct, named internal collaboration capacity, which is formed by three constructs: communication, trust, and commitment. The six hypotheses are tested and all of which were not rejected. In general, it was identified that the use of social media positively affects innovation performance and contributes to the internal collaboration capability. This dynamic capacity, in turn, positively influences the absorptive capacity and organizational agility of AgTech. Finally, these two dynamic capabilities positively impact innovation performance. As additional analyses, the existence of serial mediations in the relationship between social media and innovation performance was also verified. The results show that the internal collaboration capability and absorptive capacity, and the internal collaboration capability and organizational agility, partially mediate this relationship. The results also indicate that the explanatory power (R²) of innovation performance is higher in the proposed theoretical model compared to the direct effect of using social media. The developed and validated model allows an analytical understanding of how to improve innovation performance, indicating that there are dynamic capabilities (internal collaboration capability) that precede other dynamic capabilities (absorptive capacity and organizational agility). This and other research findings allow researchers and managers to understand the sequence and mechanisms behind innovation performance, the relevance of using social media as organizational tools, and the importance of dynamic capabilities. About dynamic capabilities, we highlight their importance both for fostering new capabilities and as drivers of innovation performance in AgTech. | en |
