SYS: Sell Your Stuff - Modeling a System that Helps Sell

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Transcript SYS: Sell Your Stuff - Modeling a System that Helps Sell

Software Architecture
Introduction
SYS:
Sell Your Stuff Modeling a
System that
Helps Sell Used
Goods
Many students and faculties of the UPenn community trash their used items
when many of these items are still in “more than desirable” conditions. The
owners of these items would most likely rather sell these items to make some
additional income than simply toss them away. However, because of reasons
such as the lack of experience or the time commitments associated with
these sales, members of the UPenn community have continued to discard
quality items. Thus, the objective is to model a potential establishment that
will effectively mitigate the entire selling process by eliminating the seller’s
need to research and monitor transactions.
Warehouse
Algorithm
Quantity
Decision Algorithms
Data Input
Result Algorithms
iniDatabase
Database Prime
Etc
How much
is left?
Vehicle
Cap
Statistics and Data
Output
General Flow
Based on our vision of how this establishment will operate, a mathematical
model was created to simulate yearly operations. Data of demand (what
students are willing to buy), supply (what students are willing to sell), costs,
and other variables associated with maintaining a business was also
gathered and analyzed. These empirical data were processed by our
business model to determine if such a business was sustainable.
Revenue
Student
Intermediary
Sell
Results and Conclusion
Where this
establishment
idea lies in the
flow
The “intermediary” box represents the SYS system which helps students
sell their used goods. Selling at the highest possible price is achieved by
the experiences and superior market knowledge. When the item is sold,
part of the revenue would go to SYS to compensate any cost generated
by the service. The rest of all the revenue would be awarded to clients.
Revenue and Cost Inputs
Advisor:
Dr. Michael Carchidi
Cost Contribution (with Item Cost)
Employee Wage (7.5%)
Transportation (0.0%)
Warehouse Rent (2.3%)
Item Cost (88.9%)
Overhead (1.3%)
Revenue Contribution
Cost Contribution
Employee Wage (67.4%)
Transportation (0.2%)
Warehouse Rent (21.0%)
Overhead (11.4%)
Time
$/time-person
Employee
Table (3.9%)
Lamp (1.1%)
Audio Sys. (5.0%)
Couch (11.4%)
Chair (1.9%)
Textbook (76.8%)
# of People
Group 9
Overhead
Utilities
Server &
Webspace
Cost
Goods
Actual (from
Housing)
# of Goods
$/Good
Profit
# of Goods
Storage Cap
Estimated (from
Survey)
Storage
Revenue
# of
Warehouses
# of Goods
Stored
$/Warehouse
Miles/Gal
Used-goods
Market
$/Mile
(vehicle specific)
$/Good (Price)
$/Gal
Transporting
Department of Electrical and
Systems Engineering
How much
to take in?
How much
was sold?
System Overview
Research/Offer
Data/Quote a
Price
Demonstrations:
April 23, 2009
RCA Lab, 11:00 – 12:00 PM
02:00 – 03:00 PM
Warehouse
Cap
How much
to store?
Demand
Want to Sell
Authors:
Fang Gao
Stephen Khou
Sungmin Lee
Items
Transportation
Algorithm
# of Vehicles
$/Vehicle
Employee costs are the primary costs associated with long term
sustainability. Item cost is unique in that it is not an attribute we can
actively reduce as it is directly tied with revenue. In addition, it is
potentially possible to create incentives for students to store their own
used-items (supply), avoiding warehouse costs. If supply and demand
remain relatively consistent in future years, should the business operate
as a typical buy-warehouse-sell establishment, the business is
sustainable under current conditions (real world data). However, this is
highly contingent on the choice of items to sell. In our study, the items
were carefully selected based on their attributes (selling price, quantity,
supply, demand) in an attempt to minimize costs. Overall, the book
selling prices is the most sensitive, mainly due to the fact that there are
a significantly larger supply and demand of books. In terms of the
additional profit that can be generated by the selling of an additional
item, the most sensitive was the desk/table category. Independence
was generally assumed.
Source: 100 Samples per Zone Distance, Collected on
12/7/04, 12/17/04, 1/19/05, 1/26/05, 4/8/05
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Content
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