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Assessment of Long-Term Effects of Marketing Mix Policies: A System Dynamics Approach

Assessment of Long-Term Effects of Marketing Mix Policies: A System Dynamics Approach

Nastaran Hajiheydari, Seyed Behnam Khakbaz
Copyright: © 2015 |Volume: 2 |Issue: 2 |Pages: 22
ISSN: 2327-3984|EISSN: 2327-3992|EISBN13: 9781466680807|DOI: 10.4018/IJSS.2015070101
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MLA

Hajiheydari, Nastaran, and Seyed Behnam Khakbaz. "Assessment of Long-Term Effects of Marketing Mix Policies: A System Dynamics Approach." IJSS vol.2, no.2 2015: pp.1-22. http://doi.org/10.4018/IJSS.2015070101

APA

Hajiheydari, N. & Khakbaz, S. B. (2015). Assessment of Long-Term Effects of Marketing Mix Policies: A System Dynamics Approach. International Journal of Systems and Society (IJSS), 2(2), 1-22. http://doi.org/10.4018/IJSS.2015070101

Chicago

Hajiheydari, Nastaran, and Seyed Behnam Khakbaz. "Assessment of Long-Term Effects of Marketing Mix Policies: A System Dynamics Approach," International Journal of Systems and Society (IJSS) 2, no.2: 1-22. http://doi.org/10.4018/IJSS.2015070101

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Abstract

Understanding of the long term effects of marketing mix policies on firm's financial outcomes is counted as an essential issue in marketing studies. Managers really need to know the efficiency of their decisions in marketing efforts. A large number of researches have been already conducted so as to disclose these consequences, although all of them have got some limitations. In the present paper, the authors have made use of system dynamics to develop a dynamic marketing system and analyze the effect of different marketing mix policies on firm's financial indicators. For this purpose, they have introduced two dynamic marketing models based on the related literature review. The first one, that is a qualitative model, represents the logic of marketing efforts based on system dynamic rules and the second one is a quantitative model which is based on five important loops of the qualitative model. The quantitative model has been manipulated in order to analyze several marketing mix policies (scenarios). The results indicate that decision making for selecting appropriate marketing mix is a complicated process usually leading to nonlinear and complex results. Considering this point, the authors' study suggests the utilization of dynamic simulation in order to predict and analyze the effects of marketing policies on firm's financial indicators. Finally, the findings clearly show the ability of system dynamics in measuring and anticipating firm's marketing initiatives and adapting the most effective policy for its success.

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