Establishing ISO 10015 accreditation system performance model for domestic enterprises
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摘要
Under Challenge 2008: Major Plans for National Development and New 10 Major Construction Projects by Council of Economic Development and Planning, talent fostering and research development will be the main consideration in the four major investments. With artificial neural network classification technology, a best network structure that eliminates over- or under-evaluation of self-assessment and actual implementation by enterprises is simulated. The accuracy rate of the module is 100% and that of sample is 98.88%. This can measure actual input and manpower training performance level of enterprises. With cross performance matrix, the researcher explores input strategies of organizations on TTQS index perception importance, expert assessment actual implementation and organization self-assessment satisfaction to find the difference of organizations on TTQS index perception important tuned into actual execution. Key questions include learning results transfer working environment, connection of training planning and operation goal achievement and training quality management system and documentation manuals, etc.Values of aspects and indexes of enterprises assessed as Group A (benchmarking) and Group B (excellent) by experts in the database through AHP questionnaire. This will be reference for enterprises on input resource strategies in TTQS index. Beginning planning, design and execution will affect results and review. After sorting in fuzzy hierarchy analysis, the researcher has Enterprise Development Strategies or Strategy Map/Blueprint (Annual Business Development Plan), including development of human resources and training planning details, themes or directions and explanations to employees.With the evaluation model, it is hoped enterprises wishing to be engaged in humanity can have self-evaluation and improve overall human resources based on the solutions in this study. Domestic enterprises can also shorten the time of introducing ISO10015, reduce cost and increase the success rate.
论文关键词:Backpropagation artificial neural network,Cross performance matrix,FAHP,ISO 10015,TTQS
论文评审过程:Available online 14 November 2009.
论文官网地址:https://doi.org/10.1016/j.eswa.2009.11.013