performance assessment of information technology based on complementary assets approach using neural networks: case study in car parts manufacturers

many researches have depicted there is no significant and positive correlation between it and firm level performance, called productivity paradox, so as successful investment on it depends on taking into account the role of complementary assets such as business processes and organizational infrastructures. on the other hand, since there are not enough resources to invest on all these assets, the investment priorities of this context should be determined. in this paper, a novel system for performance assessment of information technology is proposed which uses neural networks to determine the investment priorities of complementary assets. to study the proposed system in practice, it is used as a decision support system to determine the investment priorities on information technology and its complementary assets for 102 iranian car part manufacturers, so as complementary assets are ranked based on their contributions on firm performance.