I am trying to estimate the order-up-to level of inventory, $y_t$, according to ref [1]
$y_t = \hat{D}_t^L + z \hat{\sigma}^L_{et}$
where $\hat{D}_t^L$ is an estimate of the mean lead-time demand, $\hat{\sigma}^L_{et}$ is n estimate of the standard deviation of the $L$ period forecast error, and $z$ is a constant chosen to meet a desired service level. Assume that the retailer uses moving average to estimate $\hat{D}_t^L$ based on the demand observations from the previous $p$ periods, then
$\hat{D}_{t}^{L}=L\left(\frac{\sum_{i=1}^{p} D_{t-i}}{p}\right)$.
According to this equation, the estimated mean lead-time demand seems to only cover the demand during the lead time.
However, I checked out the definition from Lokad Quantitative Supply Chain[2], "The lead demand (also called lead time demand) is the total demand between now and the anticipated time for the delivery after the next one if a reorder is made now to replenish the inventory." This seems to mean that the mean lead-time demand should cover the demand during the lead time in this period plus the demand during the next period. This definition makes sense because assuming the safety stock factor is zero, the estimated order-up-to level is equal to the estimated lead-time demand, which should cover the demand from the current reorder time to the delivery time after the next one.
Can anyone help to clarify the definition of lead-time demand?
[1] Chen, F., Drezner, Z., Ryan, J. K., & Simchi-Levi, D. (2000). Quantifying the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information. Management science, 46(3), 436-443.