Over the years Makinuka has been producing one of the famous
mosquito repellent called ‘Refrain’ under a patent. The company’s
patent has now expired and as a result many competitors have
already started manufacturing a similar product to Refrain using
the same ingredients as well. Due to increase competition, Makinuka
is reviewing its pricing policy in order for it to remain
competitive. A research conducted in line with the proposed new
pricing policy reviewed that for every $2 decrease in price, demand
would be expected to increase by 5 000 batches, with maximum demand
for Refrain being one million batches. Each batch of Refrain is
currently made using the following materials:
Material Z: 500 grams at $.10 per gram
Material Y: 300 grams at $.50 per gram
20 minutes of machine time are required to manufacture each batch
of Refrain and the variable running costs for machine time are $6
per hour. The fixed production overhead cost is expected to be $2
per batch for the period, based on a normal budgeted production
level of 250 000 batches.
The employees possessing the skill to make Refrain have since
been moved to an anti-malaria drug project being developed by the
Pharmaceutical wing of Makinuka. Since this development is a
million dollar project, Makinuka has already obtained a
patent for this revolutionary drug which is expected to save
millions of lives. Currently, there is no other similar drug in the
market. Even though the demand of this drug is not yet known there
is great anticipation that it will receive favourable demand
worldwide
- Makinuka Ltd Is A Company That Manufactures Mosquito Repellents Over The Years Makinuka Has Been Producing One Of The F 1 (49.13 KiB) Viewed 32 times
market skimming would be the most suitable pricing strategy for
Makinuka when launching the new anti-malaria drug. (8
marks) Page 3 of
Note: Learning curve formula is Y=aX Where: Y = cumulative average time per unit to produce x units a = the time taken for the first unit of output x = the cumulative number of units produced b = the index of learning (log LR/log2) (the learning co-efficient, b=-0.321928) LR = the learning rate as a decimal