MacDonell, SGShepperd, MJ2011-08-082011-08-08200720071st International Symposium on Empirical Software Engineering and Measurement, Madrid, Spain, pages 401 - 409https://hdl.handle.net/10292/1635The availability of multi-organisation data sets has made it possible for individual organisations to build and apply management models, even if they do not have data of their own. In the absence of any data this may be a sensible option, driven by necessity. However, if both cross-company (or global) and within-company (or local) data are available, which should be used in preference? Several research papers have addressed this question but without any apparent convergence of results. We conduct a systematic review of empirical studies comparing global and local effort prediction systems. We located 10 relevant studies: 3 supported global models, 2 were equivocal and 5 supported local models. The studies do not have converging results. A contributing factor is that they have utilised different local and global data sets and different experimental designs thus there is substantial heterogeneity. We identify the need for common response variables and for common experimental and reporting protocols.(c) 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.D.2.9.b Cost estimationempirical analysis.predictionproject effortsystematic reviewConference ContributionOpenAccess10.1109/ESEM.2007.45