Matching the future capabilities of an artificial intelligence-based software for social media marketing with potential users' expectations

被引:58
作者
Capatina, Alexandru [1 ]
Kachour, Maher [2 ]
Lichy, Jessica [3 ]
Micu, Adrian [1 ]
Micu, Angela-Eliza [4 ]
Codignola, Federica [5 ]
机构
[1] Dunarea de Jos Univ Galati, Business Adm Dept, Galati, Romania
[2] ESSCA Sch Management, Angers, France
[3] IDRAC Business Sch, Lyon, France
[4] Ovidius Univ Constanta, Constanta, Romania
[5] Univ Milano Bicocca, Milan, Italy
关键词
Artificial intelligence; Machine learning; Social media marketing; Audience analysis; Image analysis; Sentiment analysis; REGRESSION-MODELS; STRATEGIES; INNOVATION;
D O I
10.1016/j.techfore.2019.119794
中图分类号
F [经济];
学科分类号
02 ;
摘要
The increasing use of Artificial Intelligence (AI) in Social Media Marketing (SMM) triggered the need for this research to identify and further analyze such expectations of potential users of an AI-based software for Social Media Marketing; a software that will be developed in the next two years, based on its future capabilities. In this research, we seek to discover how the potential users of this AI-based software (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 offer, as a way to differentiate our technological solution from other available in the market. We propose a causal model to find out which expected capabilities of the future AI-based software can explain potential users' intention to test and use this innovative technological solution for SMM, based on integer valued regression models. With this purpose, R software is used to analyze the data provided by the respondents. We identify different causal configurations of upcoming capabilities of the AI-based software, classified in three categories (audience, image and sentiment analysis), and will trigger potential users' intention to test and use the software, based on an fsQCA approach.
引用
收藏
页数:11
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