@inproceedings{16285,
  abstract     = {{To  decide  in  which  part  of  town to  open  stores,  high  street  retailers consult  statistical  data  on  customers  and  cities,  but  they  cannot  analyze  their customers’  shopping  behavior  and  geospatial  features  of  a  city  due  to  missing data.  While  previous  research  has  proposed  recommendation  systems  and decision  aids  that  address  this  type  of  decision  problem –  including  factory location  and  assortment  planning –  there  currently  is no design  knowledge available  to  prescribe  the  design  of  city  center  area  recommendation  systems (CCARS).   We   set   out   to   design   a   software   prototype   considering   local customers’  shopping  interests  and  geospatial  data  on  their  shopping  trips  for retail site selection.  With real data on 500 customers and 1,100 shopping trips, we demonstrate and evaluate our IT artifact. Our results illustrate how retailers and public town center managers can use CCARS for spatial location selection, growing retailers’ profits and a city center’s attractiveness for its citizens.}},
  author       = {{zur Heiden, Philipp and Berendes, Carsten Ingo and Beverungen, Daniel}},
  booktitle    = {{Proceedings of the 15th International Conference on Wirtschaftsinformatik}},
  keywords     = {{Town Center Management, High Street Retail, Recommender Systems, Geospatial Recommendations, Design Science Research}},
  location     = {{Potsdam}},
  title        = {{{Designing City Center Area Recommendation Systems }}},
  doi          = {{doi.org/10.30844/wi_2020_e1-heiden}},
  year         = {{2020}},
}

