Problem Chosen
F
2024
MCM/ICM
Summary Sheet
Team Control Number
2413565
Technique Innovations Terminating Illegal Wildlife Trade
The illegal wildlife trade does serious harm to global biodiversity and the balance of ecosystems,
and we urgently need more people to get involved in stopping it. Finding suitable organizations and
convincing them to participate is a great challenge.
Firstly, we constructed the client triangle prole model based on three dimensions (power,
resources, and interests), encompassed three categories of related clients: governments, enterprises,
and non-governmental organizations (NGOs). We established this model to get the scores of each
client with many indicators summarized for each dimension and then used the Entropy Weight
Method (EWM) to get the corresponding weights. Some indicators and the corresponding weights
are listed for samples as follows: country law (0.8967), industry inuence (0.2248), or media platform
promotion (0.4349) in the power dimension; GDP (0.8789), technological advancements (0.1283),
or volunteer network (0.6878) in the resources dimension; crime rate reduction and public security
(0.2540), optimizing reputation (0.1368), or biodiversity conservation (0.7460) in the interests dimen-
sion.
Secondly, we systematically evaluated the comprehensive scores of three dierent client categories
from bottom to top by utilizing the Analytic Hierarchy Process (AHP) respectively. Then we
calculated all the dierent potential client scores from 265 countries, 157 enterprises, and 30
organizations, and chose the client with the highest score. The famous luxury company, LVMH
group, with the normalized client triangle prole (0.44, 0.94, 0.24) achieves the most potential score
of 0.4157, and it is surprisingly an enterprise, neither a government nor a NGO.
Thirdly, we established a win-win model, innovatively introducing new revenue indicators such
as penalty revenues and eradication of transactions (replaceable materials). As in the case of
Apple Inc., discontinuing the use of leather products and adopting new materials has yielded more
gains. We assessed the benets that the project brings to our client through ane mapping analysis
and estimated the additional prot value ($128.06 million) in a year for LVMH. We believe this
project is ideally suitable for LVMH with its reputation for animal protection signicantly enhanced.
Additionally, we’ve devised a complementary vector model to evaluate the extra capabilities
needed by clients during project execution. The resulting complementary vector of our client LVMH is
(0.56, 0.06, 0.76), then we used the maximum matching model to identify the Seychelles govern-
ment with prole data (0.35, 0.03, 0.46) from our previously evaluated potential clients which have
the closest (99.9%) complementary vector based on cosine similarity. Our client LVMH may need
some resources such as an exclusive economic zone of nearly 1.4 million square kilometers. LVMH
can also benet from the Seychelles government’s support for wildlife protection policies, thereby
enhancing its brand image.
Finally, we established an impact model with the collected data on illegal wildlife trade from
2015 to 2022. We used multiple linear regression model based on the least squares method
to compute measurable impact from factors such as medical trade, experimental trade, food
trade, fur trade, and decoration trade, yielding coecients for the inuencing vectors of (2.651,
0.812, 0.164, -0.147, -1.811). We can decrease the future ve-year illegal wildlife trade value to $20
billion, assuming positive factors decrease by 10% annually and negative factors increase by 5%.
The model resulted in a nal predicted value of 17.54 billion, indicating a 33.81% decrease in trade
volume. We utilized a weighted probability model based on the ve-point estimation to assess
the likelihood of project success, resulting in a probability of 87.2%.
Furthermore, we put the wildlife trade within the larger ecological system and adapted the Leslie-
Gower model as a fundamental framework to elucidate the dynamics of prey-predator interactions,
the experiment results show the environmental protection factor will boost wildlife survival rates.
Moreover, when we slightly adjusted the initial trade values (±5%), the future illegal wildlife trade
value will change within 0.047%, thus it shows that our models have strong robustness.
Key Words: EWM ; AHP; Complementary Vector; Maximum Matching; Multiple Linear Regression
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