The aims are to explore the construction of the knowledge management model for engineering cost consulting enterprises, and to expand the application of data mining techniques and machine learning methods in constructing knowledge management model. Through a questionnaire survey, the construction of the knowledge management model of construction-related enterprises and engineering cost consulting enterprises is discussed. First, through the analysis and discussion of ontology-based data mining (OBDM) algorithm and association analysis (Apriori) algorithm, a data mining algorithm (ML-AR algorithm) on account of ontology-based multilayer association and machine learning is proposed. The performance of the various algorithms is compared and analyzed. Second, based on the knowledge management level, analysis and statistics are conducted on the levels of knowledge acquisition, sharing, storage, and innovation. Finally, according to the foregoing, the knowledge management model based on engineering cost consulting enterprises is built and analyzed. The results show that the reliability coefficient of this questionnaire is above 0.8, and the average extracted value is above 0.7, verifying excellent reliability and validity. The efficiency of the ML-AR algorithm at both the number of transactions and the support level is better than the other two algorithms, which is expected to be applied to the enterprise knowledge management model. There is a positive correlation between each level of knowledge management; among them, the positive correlation between knowledge acquisition and knowledge sharing is the strongest. The enterprise knowledge management model has a positive impact on promoting organizational innovation capability and industrial development. The research work provides a direction for the development of enterprise knowledge management and the improvement of innovation ability.
Abstract. This paper provides a quantitative analysis of the reduction in the bullwhip effect, and the potential benefits thanks to real-time visibility of production flows provided by the Radio Frequency Identification (RFID) technology and other technologies. This paper is based on a Fast Moving Consumer Goods (FMCG) supply chain; the supply chain is composed of there echelons, namely manufacturers, distributors and retailers of FMCG, the RFIDbased intra-SC system is implemented for the enterprise's warehouse in Jiangsu, china. The result show that RFID application can dramatically improve the efficiency of FMCG supply chain, and real-time visibility of supply chain can markedly reduce the bullwhip effect, and substantially affecting the economical profitability of the whole FMCG supply chain.
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