The nature of statistical learning theory
The nature of statistical learning theory
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
The Wealth of Knowledge: Intellectual Capital and the Twenty-first Century Organization
The Wealth of Knowledge: Intellectual Capital and the Twenty-first Century Organization
If Only We Knew What We Know: The Transfer of Internal Knowledge and Best Practice
If Only We Knew What We Know: The Transfer of Internal Knowledge and Best Practice
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining Techniques: For Marketing, Sales, and Customer Support
A comparative analysis of machine learning techniques for student retention management
Decision Support Systems
Comparative analysis of data mining methods for bankruptcy prediction
Decision Support Systems
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Knowledge management (KM) has recently emerged as a discrete area in the study of organizations and frequently cited as an antecedent of organizational performance. This study aims at investigating the impact of KM practices on organizational performance of small and medium-sized enterprises (SME) in service industry. Four popular machine learning techniques (i.e., neural networks, support vector machines, decision trees and logistic regression) along with statistical factor analysis (EFA and CFA) are used to developed predictive and explanatory models. The data for this study is obtained from 277 SMEs operating in the service industry within the greater metropolitan area of Istanbul in Turkey. The analyses indicated that there is a strong and positive relationship between the implementation level of KM practices and organizational performance related to KM. The paper summarizes the finding of the study and provides managerial implications to improve the organizational performance of SMEs through effective implementation of KM practices.