Forecasting Future Consumer Behavior: Future Research Model of Next Buying Behavior with Mixed Method Research

Document Type : Research Paper

Authors

1 Ph.D. student of Business Management, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 Professor of Business Management, Science and Research Branch, Islamic Azad University, Tehran, Iran (Corresponding Author)

3 Associate Professor of Educational Management, Science and Research Branch, Islamic Azad University, Tehran, Iran

Abstract

Nowadays, the success of businesses cannot be simplified. For this reason, consumer behavior prediction is key to success in planning and managing the environment. The focus of this research is to recognize the behavior of consumer futures in goods with high mental conflict. In fact, this study identifies factors, dimensions, components and indicators effective for future consumer shopping behavior in goods with high mental conflict and presents a structural model. In the first study, delphi method was used in four rounds to study theoretical literature and interview with 17 experts from academic and industry experts to obtain their views and fuzzy delphi logic to analyze these opinions, and in second study using a 417 - man sample and AMOS softwares and spss components were analyzed in two measurement and structural models. In the first study, two factors, four dimensions, eighteen components and sixty five indicators related to the main concept were identified and in the second study the elements of the research were analyzed using confirmatory factor analysis and finally fit the confirmed elements in the final model. The results of this study showed that feedback indices were calculated by vendors and attention to changes of products from the social impacts component with the highest amount of fuzzy norms and the least amount of fuzzy norms is the least important indicator.

Keywords

References

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Iranian Journal of Trade Studies
Volume 25, Issue 97 - Serial Number 97
January 2021
Pages 133-176

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History

  • Receive Date: 14 April 2019
  • Revise Date: 30 July 2019
  • Accept Date: 25 August 2019

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