The increasing use of Artificial Intelligence (AI) in Social Media Marketing (SMM) endows companies with strategic capabilities to understand what, where, and when to post relevant content on each social network in order to drive the maximum engagement with their audience. This trend triggered the need for this research to identify and further analyze the expectations of potential users of an AI-based platform for Social Media Marketing, which will be developed in the next two years, regarding its future capabilities. Thus, the development of reliable capabilities for the envisioned AI-based platform represents the key pillar for the strategic planning, conceptual design and software development process. In this research, we seek to discover how the potential users of this AI-based platform (owners and employees from digital agencies based in France, Italy and Romania, as well as freelancers from these countries, with expertise in SMM) perceive the capabilities that we propose to differentiate this technological solution from other available on the market. On the one hand, we propose a causal model to test which expected capabilities of the future AI-based platform can explain potential users’ intention to test and use this innovative technological solution for SMM, based on integer valued regression models. In this way, R software is used to analyze the data provided by the respondents. On the other hand, we identify the most influential predictors of potential users’ intention to test and use the software, based on an fsQCA causal configurations’ approach. Software experts who will be in charge of the AI-based platform development are advised to act in meaningful way accordingly to these findings, to avoid pitfalls that can threaten the software development process

Capatina, A., Kachour, M., Lichy, J., Micu, A., Micu, A., Codignola, F. (2019). Matching the future capabilities of an Artificial Intelligence-based platform for Social Media Marketing with potential users’ expectations. Intervento presentato a: INEKA Conference, Knowledge, Business, and Innovation. Economies and sustainability of future growth, Verona, Italy.

Matching the future capabilities of an Artificial Intelligence-based platform for Social Media Marketing with potential users’ expectations

Codignola, F
2019

Abstract

The increasing use of Artificial Intelligence (AI) in Social Media Marketing (SMM) endows companies with strategic capabilities to understand what, where, and when to post relevant content on each social network in order to drive the maximum engagement with their audience. This trend triggered the need for this research to identify and further analyze the expectations of potential users of an AI-based platform for Social Media Marketing, which will be developed in the next two years, regarding its future capabilities. Thus, the development of reliable capabilities for the envisioned AI-based platform represents the key pillar for the strategic planning, conceptual design and software development process. In this research, we seek to discover how the potential users of this AI-based platform (owners and employees from digital agencies based in France, Italy and Romania, as well as freelancers from these countries, with expertise in SMM) perceive the capabilities that we propose to differentiate this technological solution from other available on the market. On the one hand, we propose a causal model to test which expected capabilities of the future AI-based platform can explain potential users’ intention to test and use this innovative technological solution for SMM, based on integer valued regression models. In this way, R software is used to analyze the data provided by the respondents. On the other hand, we identify the most influential predictors of potential users’ intention to test and use the software, based on an fsQCA causal configurations’ approach. Software experts who will be in charge of the AI-based platform development are advised to act in meaningful way accordingly to these findings, to avoid pitfalls that can threaten the software development process
paper
Artificial Intelligence, Machine Learning, Social Media Marketing, audience analysis, image analysis, sentiment analysis
English
INEKA Conference, Knowledge, Business, and Innovation. Economies and sustainability of future growth
2019
2019
none
Capatina, A., Kachour, M., Lichy, J., Micu, A., Micu, A., Codignola, F. (2019). Matching the future capabilities of an Artificial Intelligence-based platform for Social Media Marketing with potential users’ expectations. Intervento presentato a: INEKA Conference, Knowledge, Business, and Innovation. Economies and sustainability of future growth, Verona, Italy.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/220112
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