A hybrid proposal for cross-sectoral analysis of knowledge management

作者：Herrero Alvaro; Saiz Barcena Lourdes; Manzanedo Miguel A; Corchado Emilio

来源：Soft Computing, 2016, 20(11): 4271-4285.

DOI：10.1007/s00500-016-2293-9

• Knowledge management
• Hybrid artificial intelligence system
• Unsupervised neural networks
• Exploratory projection pursuit
• Classification trees

At present time, although many theoretical formulations have been successfully proposed, there is a lack of ICT-based tools to support practical deployment of knowledge management (KM) in real settings. To bridge this gap, a hybrid artificial intelligence system is proposed in present study, aimed at gaining deeper knowledge about KM practices in four different economic sectors. By means of soft computing, companies are diagnosed according to their status regarding KM and subsequent explanations about crucial KM practices and perspectives are generated. Interesting conclusions are then derived from these explanations, allowing KM managers to optimise their decisions and obtain better results. Experimental results of real-life data from Spanish companies associated with different economic sectors validate the proposed combination of techniques.

• 出版日期2016-11