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Motivation & Negative Contribution Margin

Negative margins are usually a consequence of the inability of the firm to control costs or more global problems: macroeconomic, government, or industry difficulties beyond the control of the company. If we analyze the reasons in more detail, then we can highlight the following. First, a spike in commodity prices can make costs significantly higher than margins if the sale is long enough. This factor is not regulated by the organization and is a signal for the firm to redistribute available internal resources. Secondly, it is the development of technologies that supplant their progenitors. It means, for example, that the buggy industry suffered severe damage in the development of the combustion engine (Daily et al., 2017). Furthermore, now, electric cars could potentially displace gasoline-fueled cars in the future.

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For intentional or motivated action, the reasons may differ. Standardizing prices by benchmarking is a reasonably deep approach that includes many analytical tools (Sekhar & Rajagopalan, 2012). Compared to the standards, the specified seller can agree to a negative contribution margin in the following cases. First, it can be the imposition of a fight on competitors to get rid of them. Secondly, these activities can be carried out in the off-season of this group of goods to keep the profit. Third, the excess of expenses over income for a specific type of product reduces the amount of taxes paid by the firm (Liu et al., 2020). Finally, this event can be compared to dumping, which is regulated at the state level and, in general, hurts the market of manufacturers and sales. Typically, it is used to capture a market segment and fight competitors, as indicated in the reasons for this case. The periodic nature of these events speaks of a great goal that will be achieved only by such constant steps. A deeper analysis through modeling can reveal more statistics for interpretation (Wang et al., 2020). However, given the amount of information, conclusions can only be drawn in general terms.


Daily, M., Medasani, S., Behringer, R., & Trivedi, M. (2017). Self-driving cars. Computer, 50(12), 18-23.

Liu, B., Cao, Y., Lin, Y., Li, Q., Zhang, Z., Long, M., & Hu, H. (2020). Negative margin matters: Understanding margin in few-shot classification. In European Conference on Computer Vision (pp. 438-455). Springer, Cham.

R.C. Sekhar L. R., & Rajagopalan, A. (2012). Management accounting. OUP India.

Wang, S., Wang, X., & Zhang, J. (2020). Robust optimization approach to process flexibility designs with contribution margin differentials. Manufacturing & Service Operations Management. 

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