designing a fuzzy inference system for predicting the implementation success of erp solution
Authors
abstract
implementation of enterprise resource planning has had a chaotic history in which many projects ended successfully and many failed or ended without approaching the predetermined objectives. this research, in terms of purpose, is considered fundamental since it designs a new system for solving a fundamental problem and it is also an applied research because the research result is deployed in the organization for determining the implementation success ratio. the research utilizes the content analysis for identifying the factors and indicators and uses a survey research for gathering data from selected organizations. in this study, for overcoming the problems of implementation project, a fuzzy system has been designed, trained and validated using the adaptive neuro-fuzzy inference system so as to predict the implementation success ratio before the initiation of the project. the research output is an intelligent fuzzy inference system.
similar resources
A Multiple Adaptive Neuro-Fuzzy Inference System for Predicting ERP Implementation Success
The implementation of modern ERP solutions has introduced tremendous opportunities as well as challenges into the realm of intensely competent businesses. The ERP implementation phase is a very costly and time-consuming process. The failure of the implementation may result in the entire business to fail or to become incompetent. This fact along with the complexity of data streams has led ...
full textdesigning a fuzzy expert system for erp selection
the selection of erp systems has been considered as one of the most influential and risky managerial decisions due to its heavy burden of purchase and implementation costs. the purpose of this paper is designing a fuzzy expert system for selecting the appropriate erp system based on the internationally selected and validated criteria for minimizing the risks of inappropriate selection. if an op...
full textAdaptive Neural Fuzzy Inference System Models for Predicting the Shear Strength of Reinforced Concrete Deep Beams
A reinforced concrete member in which the total span or shear span is especially small in relation to its depth is called a deep beam. In this study, a new approach based on the Adaptive Neural Fuzzy Inference System (ANFIS) is used to predict the shear strength of reinforced concrete (RC) deep beams. A constitutive relationship was obtained correlating the ultimate load with seven mechanical a...
full textCritical Success Factors for ERP System Implementation
As more and more enterprises move from functional to process-based IT infrastructure, ERP system becomes one of today’s most widely used IT solutions in many large enterprises. In spite of the widely used IT solutions, many ERP implementations are not successful. It takes longer time and costs more money than expected. Given the large investment that an ERP project requires and the potential be...
full textdesigning an adaptive nuero-fuzzy inference system for evaluating the business intelligence system implementation in software industry
the main goal of research is designing an adaptive nuero-fuzzy inference system for evaluating the implementation of business intelligence systems in software industry. iranian software development organizations have been facing a lot of problems in case of implementing business intelligence systems. this system would be helpful in recognizing the conditions and prerequisites of success or fail...
full textDesigning a Fuzzy Inference System to Estimate the Scores of Assessment Centers
One of the methods used to measure and evaluate employees is the assessment center. Assessment centers usually have good validity at the instrumental level, but have weaknesses at the summation level. This research seeks to provide a fuzzy system for estimating AC final scores based on competency, intelligence and personality scores by modeling mentality of experts in this field. For this purpo...
full textMy Resources
Save resource for easier access later
Journal title:
مدیریت فناوری اطلاعاتجلد ۵، شماره ۱، صفحات ۹۸-۱۰۶
Keywords
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023