01166nas a2200157   4500008004100000245007000041210006900111260000900180300001200189490000800201520062900209653002300838100001900861700001500880856011300895       2019                        eng d00aBusiness Performance Prediction in Location-based Social Commerce0 aBusiness Performance Prediction in Locationbased Social Commerce  c2019  a112-1230 v1263 aSocial commerce and location-based services provide a data platform for coexisting and competing businesses in geographical neighborhoods. Our research is aimed at mining data from such platforms to gain valuable insights for better support to strategic and operational business decisions. We develop a computational framework for predicting business performance that takes into account both intrinsic (e.g., attributes) and extrinsic (e.g., competitions) factors. Our experiments on synthetic and real datasets demonstrated superiority of a hybrid prediction model that adopts both link-based and context-based assumptions.10aBusiness Analytics1 aChang, Xiaohui1 aLi, Jiexun  uhttps://stage.business.oregonstate.edu/biblio/business-performance-prediction-location-based-social-commerce