Relationship between marketing strategy and profitability in industrial firms: Evidence from Jordan

  • Received February 6, 2023;
    Accepted March 13, 2023;
    Published April 6, 2023
  • Author(s)
  • DOI
  • Article Info
    Volume 19 2023, Issue #2, pp. 17-26
  • Cited by
    2 articles

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This work is licensed under a Creative Commons Attribution 4.0 International License

A marketing strategy is a firm’s overall plan for reaching prospective consumers and turning them into permanent customers of their services or products. This paper aims to investigate the link between profitability and marketing strategy to understand how firm profitability influences marketing strategy. Moreover, it assesses the impact of return on assets (ROA) on the company’s marketing strategy. The study uses random effect regression models; a marketing strategy is measured using a sales expenses ratio, which equals sales expenses over total assets. The firm size is a control variable represented by the total sales normal logarithm. The study sample comprises Jordanian industrial shareholder companies; the analysis period is from 2005 to 2020. The study collected 808 annual observations. The findings reveal that ROA has a statistically significant effect on marketing strategy, but its components have no effect. The adj-R2 (the explanatory power) for model 1 is 18.8%, and for model 2 is 11.4%. Therefore, the main conclusion is that ROA components do not have any incremental information content in explaining the marketing strategy variance. The study recommends industrial firms in Jordan increase their profitability by adopting a diverse marketing strategy, focusing on customer satisfaction, investing in market research, using social media, and developing a strong brand image.

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    • Table 1. Study variables
    • Table 2. Descriptive results
    • Table 3. Pearson correlation matrix
    • Table 4. Spearman correlation matrix
    • Table 5. Results for the first model
    • Table 6. Results for the second model
    • Table 7. OLS findings for the study models
    • Table 8. Coefficients for the second model
    • Table 9. Husman Test
    • Table 10. Random effect model results
    • Conceptualization
      Mohammad Fawzi Shubita
    • Data curation
      Mohammad Fawzi Shubita
    • Formal Analysis
      Mohammad Fawzi Shubita
    • Funding acquisition
      Mohammad Fawzi Shubita
    • Investigation
      Mohammad Fawzi Shubita
    • Methodology
      Mohammad Fawzi Shubita
    • Resources
      Mohammad Fawzi Shubita
    • Writing – original draft
      Mohammad Fawzi Shubita
    • Writing – review & editing
      Mohammad Fawzi Shubita