TY - JOUR
T1 - Effort Estimation for ERP Implementation Projects Using Social Choice - A Comparative Study
AU - Koch, Stefan
AU - Mitlöhner, Johann
PY - 2010/10/1
Y1 - 2010/10/1
N2 - ERP implementation projects have received enormous attention in the last years, due to their importance for organisations, as well as the costs and risks involved. The estimation of effort and costs associated with new projects therefore is an important topic. Unfortunately, there is still a lack of models that can cope with the special characteristics of these projects. As the main focus lies in adapting and customising a complex system, and even changing the organisation, traditional models like COCOMO can not easily be applied. In this article, we will apply effort estimation based on social choice in this context. Social choice deals with aggregating the preferences of a number of voters into a collective preference, and we will apply this idea by substituting the voters by project attributes. Therefore, instead of supplying numeric values for various project attributes, a new project only needs to be placed into rankings per attribute, necessitating only ordinal values, and the resulting aggregate ranking can be used to derive an estimation. We will describe the estimation process using a data set of 39 projects, and compare the results to other approaches proposed in the literature.
AB - ERP implementation projects have received enormous attention in the last years, due to their importance for organisations, as well as the costs and risks involved. The estimation of effort and costs associated with new projects therefore is an important topic. Unfortunately, there is still a lack of models that can cope with the special characteristics of these projects. As the main focus lies in adapting and customising a complex system, and even changing the organisation, traditional models like COCOMO can not easily be applied. In this article, we will apply effort estimation based on social choice in this context. Social choice deals with aggregating the preferences of a number of voters into a collective preference, and we will apply this idea by substituting the voters by project attributes. Therefore, instead of supplying numeric values for various project attributes, a new project only needs to be placed into rankings per attribute, necessitating only ordinal values, and the resulting aggregate ranking can be used to derive an estimation. We will describe the estimation process using a data set of 39 projects, and compare the results to other approaches proposed in the literature.
UR - http://www.informaworld.com/smpp/content~content=a925506771~db=all~jumptype=rss
M3 - Journal article
SN - 1751-7575
VL - 4
SP - 265
EP - 281
JO - Enterprise Information Systems
JF - Enterprise Information Systems
IS - 3
ER -