Identify and Clustering Challenges of knowledge-based Enterprises using ANN and BPMS Approaches; Case study: Yazd KBEs

Knowledge always is a powerful tool in stabilizing position of individual/community service to the public and excellence approach in current autonomous communities. Value of knowledge has been more necessary if it capable for transfer to the High-Tec and needed Technologies of humanity societies. Knowledge Based Enterprise (KBE) is a real-law enterprise such as factory that transfer Knowledge to production/services. However KBEs are causing for sustainable knowledge economy and development native knowledge in more countries, but these enterprises havnt optimize occasion in view of quantity, production quality and service extensive according to the 20 years growth view of Iran. Purpose of this study is to identifying encounter challenges of KBEs that located on Yazds Science and Technology Park (STP) and clustering these challenges with ANN method exactly. The Samples contains 137 person such as manager and top employees of these enterprises. Number of reached challenges have been 59 that were attained from literature and experts guidelines were designed and distributed between samples suddenly. According to the PB artificial neural network, reliabilities of samples were confirmed with MSE=2.0332 and priority done with Multilayer Perceptron (MLP) artificial neural network and with inspiration of Business Process Management System (BPMS) approach. According to the BPMS approach and MLP method, Result show that challenges did cluster in three factions known as: management activities, operational activities and support activities. Thus, number of management, operational and support activities in order were 27, 15 and 17 items exactly.