Presenting a strategic model of marketing capacities and its impact on performance in order to develop open innovation in Khuzestan steel industry

Marketing capacity is a mechanism that enables organizations to implement their strategies in a competitive environment. Using these capabilities, organizations can improve their performance in today's competitive environment by using their physical resources and intellectual and strategic assets. The purpose of this study is to present a model of marketing capacity in the Khuzestan steel industry and its impact on the company's performance in developing open innovation.

The method of the present study is a combination that was performed in two qualitative and quantitative stages using data theory of the foundation. Qualitative stage data were collected through interviews with 15 experts in the field of marketing who were selected through purposive sampling and analyzed with Maxqda software. Qualitative data analysis software.

The results obtained from the analysis of theoretical foundations and research interviews, led to the final model of marketing capacity, which has 10 main categories of product, distribution network, market, customer, competitor analysis, advertising, brand, management strategies, and technological strategies. And training. Analysis of competitors, customers and products in the role of "underlying factors" of the market in the role of "environmental conditions", advertising, brand, distribution network, management strategies, technological strategies and training in the role of "strategies and strategies" and marketing capacity in the role of the "main category" and the company's performance in the role of "consequence" have been identified. The researcher-made marketing capacities that resulted from the results of the qualitative sector and in the quantitative sector, considering the importance of open innovation to be a market leader in the steel industry, the company's performance was measured based on open innovation. Was analyzed. Findings indicated a good fit of the proposed model.