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Abstract
We survey recent articles on mobile promotion and propose guidance on the usage of mobility models for such promotion. Our paper identifies human mobility features, including geo-spatial contexts and hypercontexts, and surveys localization tools for collecting such mobility data. It overviews the machine learning and deep learning algorithms on human mobility and develops guidelines for the selection of predictors based on the type of mobile-promotion question as well as the mobility characteristics, context, and underlying nature of data. To the best of our knowledge, our paper is the first to synthesize how mobile promotions can systematically leverage the range of contextual and hyper-contextual attributes underlying human mobility and to provide a parsimonious set of guidelines on effectively using mobility prediction techniques for mobile promotions.
Recommended Citation
Zhao, Kai; Xiao, Houping; and Rai, Arun, "Toward Effective Mobile Promotion: A Survey of Mobile Prediction Techniques and Applications" (2020). AMCIS 2020 Proceedings. 22.
https://aisel.aisnet.org/amcis2020/data_science_analytics_for_decision_support/data_science_analytics_for_decision_support/22
Toward Effective Mobile Promotion: A Survey of Mobile Prediction Techniques and Applications
We survey recent articles on mobile promotion and propose guidance on the usage of mobility models for such promotion. Our paper identifies human mobility features, including geo-spatial contexts and hypercontexts, and surveys localization tools for collecting such mobility data. It overviews the machine learning and deep learning algorithms on human mobility and develops guidelines for the selection of predictors based on the type of mobile-promotion question as well as the mobility characteristics, context, and underlying nature of data. To the best of our knowledge, our paper is the first to synthesize how mobile promotions can systematically leverage the range of contextual and hyper-contextual attributes underlying human mobility and to provide a parsimonious set of guidelines on effectively using mobility prediction techniques for mobile promotions.
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