Expert Systems with Applications, 34 (4), 2008 – interesting articles
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[Deutscher Titel: Expert Systems with Applications, 34 (4), 2008 – interessante Artikel]

An empirical study of the effects of knowledge sharing and learning behaviors on firm performance 2342-2349
Chuck C.H. Law and Eric W.T. Ngai

  • Abstract: Knowledge sharing and learning behaviors in the workplace are believed to be very important to the success of firms. In this study, the relationships between knowledge sharing and learning behaviors, business process improvement, product and service offerings, and organizational performance are examined based on a sample of 134 firms engaged in manufacturing, and wholesale or retailing operations. Data analyses using the partial least squares statistical technique revealed that knowledge sharing and learning behaviors are positively associated with business process improvement, and product and service offerings. Business process improvement and product and service offerings are positively associated, and they in turn are positively related to organizational performance. The findings reinforce the importance of knowledge sharing and learning to companies. Executives should encourage knowledge management and organizational learning activities within their firms, and give proper considerations to the strategies and implementation of programs supporting these activities in order to enhance firm performance.
  • Keywords: Knowledge sharing; Learning organization; Business process improvement; Product and services offerings; Organizational performance
  • doi: 10.1016/j.eswa.2007.03.004  

A novel approach for discovering retail knowledge with price information from transaction databases 2350-2359
Yen-Liang Chen, Tony Cheng-Kui Huang and Sih-Kai Chang

  • Abstract: With the advances in information technology and the emergence of Internet commerce, analysis of transaction data has become a crucial technique for effective decision-making and strategy formation in business operations. It is especially critical for retail management, in both online and brick-and-mortar stores. Traditional research in mining retail knowledge, however, does not take into account the products’ prices and how such settings can affect potential demand. This paper opens a new research dimension by treating products’ prices as an important decision variable in mining retail knowledge. To the best of our knowledge, the problem addressed in this paper has never been dealt with in existing research papers. We propose a representation scheme to incorporate price information into historical transaction data. An efficient algorithm is developed to “dig” out implicit, yet meaningful, patterns with price information. In addition, an extensive and well-designed experiment is executed, showing that the algorithm is computationally efficient and that the proposed analysis is significant and useful.
  • Keywords: Association rules; Data mining; Price; Retailing management
  • doi: 10.1016/j.eswa.2007.03.006 

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Copyright © 2008 Elsevier B.V. All rights reserved.


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