The BDL expects a decrease of a dispatched object's value for individuals, when delivered asynchronously.
Morgan,[1] Savage [2] and others provided approaches of probability to cope with the risk of the processing task in vain.
Expected value of including uncertainty (EVIU) is a similar concept focusing on information and decision making.
In real world scenarios objects are typically raw and industry goods but can also be services or pure information.
This type of function might apply, for example, if a depreciation is coupled to a risk factor, which denotes the sheer chance that other consumers take note of the new dispatched object.
For example, on a social platform a supplier of sports gear promises the first 20 callers a free bicycle helmet.
In other words, appreciation and depreciation occur once or multiple times as values in the x-axis (t) change.
Bulk depreciation is often applied among competitive actors, who consume the same information units and/or resources.
In general and for non-polynomial depreciation functions, a faster reaction results in a beneficial outcome for the individual competitor.
The term "BDL" arose from an academic deliverable of a student, Brayan Zimmerli, at the University of Zurich in 2013.
The deliverable's core research question was to mitigate the unfairness of data delivery to multiple subscribers of a topic.