Document Type : Original Article


1 Ph.D Candidate of Department of Technology Management, Science and Research Branch, Islamic Azad University,Tehran, Iran

2 Assistant Professor, Department of Industrial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran

3 Assistant Professor, Department of Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran

4 Assistant Professor, Department of Management, Shiraz Branch, Islamic Azad University, Shiraz, Iran


Automotive industry particularly, commercial automotive industry, ranks as a key industry in the economic growth. The necessity of investigating the research & development(R & D) activities of digital marketing and innovation in the form of a dynamic system in automotive industry based on the 3 variables: empowerment of supply network, of product innovation, and of digital marketing is quite undisputed. The present research has been done with a view to identifying and evaluating the cause-and-effect interdependent relations governing the variables of R & D of digital marketing and innovation in commercial automotive industry. The research is typically applied, and has been done using the descriptive-survey method. The research community consisted of 50 experts; all with acceptable academic backgrounds and years of experience as executive managers and marketeers in the R & D of automotive industry. To analyze the data, the views of some elected experts on automotive industry, along with Delphi fuzzy and Dematel method were applied. Our findings showed that the variable “Intensity of R & D of digital marketing and innovation” has the most effect on the other variables. The variable “Empowerment of supply network” with the score of 3,25 has the largest amount of interaction with the other variables. Also, the variable “ Empowerment of R & D in digital marketing and innovation” with the score of 1,08 has the smallest amount of interaction with the other variables.


Aníbal, N. C., & Gonzalo, F.S.(2017). Principal researcher and project manager: who should drive R&D projects?. R&D Management. 47(2), 277-287.
Arun, A. Elias., Robert, Y., Cavana & Laurie,S.  (2002). Stakeholder analysis for R&D project management. R&D Management.32(4), 301-310.
Barragán, O.A., & Zubieta, G.J.(2018). Critical Factors toward Successful R&D Projects in Public Research Centers: a Primer.  Applied Research and Technology, 11(6), 866–875.
Coyle, G., & Exelby, D. (2000). The validation of commercial system dynamics models. System Dynamics Review, 16(1), 27 – 41.
Daim, T.U., Gulgun, K., & Cowa, K.(2017). Developing Oregon’s renewable energy portfolio using fuzzy goal programming model. Computers & Industrial Engineering. 59, 786-793.
Daneshzand , F., Amin-Naseri , M.R., Asali, M., Elkamel, A. & Fowler, M. (2019). A System Dynamics Model for Optimal Allocation of Natural Gas to Various Demand Sectors. Computers and Chemical Engineering. 118, 709-723.
Dorota, K., &  Dorota, S.(2016). Classification of R&D projects and selection of R&D project management concept. R&D Management. 46(5), 831-841.
Félix, J., López. I., Emilio, J., & López, M.(2017). Institutional framework, corporate ownership structure, and R&D investment: an international analysis.R&D Management. 47(1), 141-157.
Gasbi, S., & Chkir, A.(2016). Research and Development (R&D) Spillovers and Economic Growth: Empirical Validation in the Case of Developing Countries. Journal of Economics and International Finance. 4(5), 107–122.
Ghasinoory, S., Amiri, M.,& Alizadeh .P.(2017). A Study of the Factors Affecting the Cost of Iranian Business Sector in Research and Development Activities; Study of three different industries.Technology Development Management. 4(2) ,22-44.
Hans, J. T.(2003) Managing innovative R&D teams, R&D Management. 33(3)
Huang, C.C., Chub, Pung, Y., & Chiang, Y. H. (2008). A fuzzy AHP application in government-sponsored R&D project selection. Omega. 36, 1038-1052.
Huang, C.C., Chub, Pung, Y., & Chiang, Y. H. (2008). A fuzzy AHP application in government-sponsored R&D project selection. Omega. 36, 1038-1052.
Juite, W.(2017). Structuring innovation funnels for R&D projects under uncertainty. R&D Management. 47(1), 127-140.
Juliana, H., & Volker, M.(2011). Outsourcing R&D: a review, model, and research agenda. R&D Management.41(1),1-7.
Jung, U., & Seo, D.(2010).  An ANP approach for R&D project evaluation based on interdependencies between research objectives and evaluation criteria, Decis. Supp. Syst. 49 (3), 335–342.
Kaisa, H., Pia H. L.,& Paavo, R.(2016). Managing the appropriability of R&D collaboration, R&D Management. 46, (S1), 145-158 .
Latipova, A.( 2015), On optimization of R&D Project Selection and Scheduling. IFAC-Papers On Line 48-25, 006–010.
Linton, J.D., Walsh, S.T., Kirchhoff, N.A., Morabito, J.M., & Merges, M.J. (2000). selection of R&D Project in a Portfolio. Proceedings of the 2000 IEEE. 506-511.
Martha, L., Torres,B ., Rebeca, M. D.,& Felipe H.P.(2016). Technological impact of R&D grants on utility models.R&D Management. 46(S2), 537-551.
Meade, L., & Presly, A.(2002). R&D project selection Using the Analytic Network process. IEEE Transactions on Engineering Management. 49(1), 59-66.
Oliver, G., Edmund, C., Salzmann., & Alexander, K .(2019). university‐industry collaboration and frontend success: the moderating effects of innovativeness and parallel cross firm collaboration. R&D Management.49(5), 835-849.
Samadi, M .Y., Hashemzadeh, K. G., Radfar, R.,& Manteghi, M.(2017). Investigating the importance of empowerment factors of research and development centers on technology transfer methods in investment (Case study: Iranian automotive industry). Investment knowledge. 6(3), 68-83( in Persian).
Shah Hosseini, M., Heidari, A., Arabi, M.&, Qaderi,  K .S.(2017). Presenting a Model for Managing Strategic Unions of Research and Development in the Automotive Industry of Iran. Business Management . 11(2), 39-58( in Persian).
Sterman, J. D. (2000). Business dynamics, systems thinking and modeling for the complex world. Boston: McGro.23(2),165-189.
Thomas, L., & Peter, S.(2013) Managing the manufacturing–R&D interface in the process industries .R&D Management. 43(3), 252-270.
Yan, Chen.(2018).Partial adjustment toward target R&D intensity. R&D Management. 48(5), 591-602.
Yu, Q.Z.(2017) Why and how knowledge sharing matters for R&D engineers. R&D Management .47(2), 212-222.