Can Sales Uncertainty Increase Firm Profits?

Autor: James D. Hess, Ying Yang, Niladri B. Syam
Rok vydání: 2016
Předmět:
Zdroj: Journal of Marketing Research. 53:199-206
ISSN: 1547-7193
0022-2437
Popis: The authors add to the sales management literature in three ways. First, they demonstrate that a firm can benefit from higher sales uncertainty. This is contrary to the finding from the standard principal–agent models that more sales uncertainty hurts the firm when agents are risk-averse. Second, the authors find that the risk-averse agent's total pay can increase when there is high sales uncertainty, and this too is contrary to the standard principal–agent model. Third, they provide intuition for this surprising result by showing that it holds when the slope of the sales response function is random but not when the intercept is random. When the responsiveness (slope) of sales to a decision variable (of the firm or the agent) is random, information about randomness becomes decision-relevant and the firm can exploit learned information. In this study's model, the agent and firm can receive noisy signals of random demand. When the customers’ response to effort (or price) is random, the decision about effort (price) responds optimally to information in a way that benefits the firm. When uncertainty is high, there is more potential information for the firm to exploit profitably, owing to the convexity of the sales with respect to the uncertainty parameter. This is enough to dominate the negative impact of uncertainty owing to agents’ risk aversion. When randomness affects only baseline sales (intercept), received signals are not decision-relevant. In that case, higher uncertainty has only a negative impact, just as in standard principal–agent models.
Databáze: OpenAIRE