کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
10322015 660811 2014 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Organizational learning networks that can increase the productivity of IT consulting companies. A case study for ERP consultants
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Organizational learning networks that can increase the productivity of IT consulting companies. A case study for ERP consultants
چکیده انگلیسی
This paper considers the use of social learning networks to increase the productivity of IT consulting companies. We advocate that using a carefully designed social learning network can reduce the learning time for enterprise software developers and consultants. By viewing learning as a social act, a consulting company can increase its productivity. Increased productivity is based on hastening the learning process. The focus of this paper is to identify the ways in which social networks catalyze the process of knowledge sharing in order to increase the productivity in the enterprise resource planning (ERP) consulting sector. We present a set of detailed practical results that were obtained from experiments with an original knowledge sharing method that was applied to training young software developers to enable them to work for some of the world's most demanding IT companies. The experimental data were collected from 2004 to 2011 during 12 training sessions conducted by an IBM partner in conjunction with the Computer Science Department of a large Eastern European University. The main results of this study were: (1) designed a learning community that reduced the time needed to insert junior consultants into ERP projects; and (2) statistical data were generated that measured the increase in productivity that an ERP consulting company could obtain by employing organizational learning networks. We also discuss the positive impacts of social networks that can be established between private companies and universities.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 41, Issue 1, January 2014, Pages 126-136
نویسندگان
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