The Prediction of the Success of New Product Development Using the Combination of Factor Analysis and Artificial Neural Network

Subject Areas : Business Management

Gholamraza  Soltani Fesaghandis ¹ (دانشجوی دکتری مدیریت تحقیق در عملیات، پردیس بین‌الملل، دانشگاه فردوسی مشهد)
Alireza  Pooya ² (دانشیار دانشکده علوم اداری و اقتصاد، گروه مدیریت دانشگاه فردوسی مشهد)
Mostafa  Kazemi ³ (استاد دانشکده علوم اداری و اقتصاد، گروه مدیریت دانشگاه فردوسی مشهد)
Zahra  Naji Azimi ⁴ (دانشیار دانشکده علوم اداری و اقتصاد، گروه مدیریت دانشگاه فردوسی مشهد)

Received: 2016-02-05 Accepted : 2016-06-04 Published : 2016-08-22

Keywords: Artificial Neural Network, factor analysis, Success of new product development,

Abstract :

The success of new products is as the greatest element for the company's success and even their survival. However, numerous studies show that the failure rate of new product development as a fundamental problem in many companies has been raised. Many companies are trying to predict the success of the development of new product before its development. The aim of this study was to predict the success of new product development using a combination of factor analysis and artificial neural network in the food and beverage industry. This research based on purpose is practical and based on method is descriptive. The population of this research is the food and beverage manufacturers in the province of East Azerbaijan in 1394. In order to collect data two questionnaires have been distributed among the population after the validity and reliability assessments. In order to analyze the data in this study, factor analysis and artificial neural network is used. Analysis of the data revealed the presence of six main structures as factors in the success of new product development: conceptualization of new product, market orientation, design orientation, technology orientation, use of sources, and management of new product development as the effective elements in the development of the success of new product. Furthermore, the prediction of the success of new product’s development using neural networks shows that the designed network was able to predict the success of the development of new product correctly.

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