Explaining the Mediating Role of Innovation in Relationship Between Knowledge Management and Competitive Advantage of SMEs Using Neural Network and Structural Equation Modeling Approach

Document Type : Production & Operations Management

Authors

1 MA student in Executive Management, Faculty of Management and Accounting, Rasht Branch, Islamic Azad University, Rasht, Iran

2 Assistant Professor in Industrial Management, Faculty of Management and Accounting, Rasht Branch, Islamic Azad University, Rasht, Iran

Abstract

Although small and medium-size enterprises (SMEs) constitute more than 85 percent of total business enterprises in Iran, most of the knowledge management studies concentrated on large enterprises. In this way, this study investigated the relationship between knowledge management, innovation (technology and marketing), and competitive advantage in SMEs. The statistical population of the study consists of SMEs in Rasht industrial parks which 124 out of them were selected based on the random sampling method. The collected data by a designed questionnaire were analyzed using structural equation modeling (SEM) and artificial neural network techniques. The results of data analysis based on Partial Least Square (PLS) indicate that knowledge management has positive and significant relationships with technological innovation and marketing innovation. In addition, knowledge management has a positive and significant relationship with a competitive advantage and its strongest relationship with competitive advantage mediated by technological innovation, So, technology innovation is a strong mediator between knowledge management and competitive advantage. On the other hand, the results of the neural network approach show that technology development is the most important predictor of a competitive advantage which this finding is consistent with the output of PLS analysis. Some suggestions also are provided for further researches and application in a statistical population.

Keywords

References

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History

  • Receive Date: 24 January 2020
  • Revise Date: 17 September 2020
  • Accept Date: 13 October 2020

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