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Food Waste Reduction
Referring to the current situation in Peru concerning the high rate of food waste, the best solution is to distribute the restaurants remaining food to people from disadvantaged and broken families. It is the best option and initiative that has multiple directions. The first one is that it can reduce the immense negative impact on the environment it causes (Bedoya-Perales et al. 4). The second one is that restaurant remaining food can be donated to people from disadvantaged and broken families who are on the edge of poverty. It is the manifestation of a goodwill gesture, as restaurant stakeholders spend their own finances to support second-class treatment.
Delivering of Restaurant Remaining Food to People from the Lower Social Class in Peru
According to the latest research, the majority of Peruvians live near starvation. They cannot afford substantial meals and eat only once a day due to a lack of financial resources (Malerba et al. 3). In contrast, entertainment facilities, such as restaurants, cannot recycle and reuse all food leftovers they have. There is a decision to allocate all restaurant remaining food of good quality to marginalized segments of people. It is the best option to satisfy impoverished individuals needs in terms of social policy and get rid of environmental issues. Food waste is a current issue nowadays, making people suffer and survive. Peruvian entrepreneurs offer their helping hands and different benefits to set role models for foreign countries that have the same problem.
Geographic Boundaries of the Market
There has to be a distribution within restaurants or cafes that must be in charge of catering their services to representatives of one particular community. There are 25 regions in Peru, so every single region has to assign two restaurants as food delivery centers for poor Peruvians (Daneshvar et al. 1). It is a case of the governmental program that rewards the restaurant stakeholders and reduces the inequity gap among human beings.
Competition
In this case, there can be no competition, as all restaurants have to work collaboratively and incorporate donating policies as they are the members of the charitable governmental program facilitating the social institute improvement.
Market Size
According to the statistics, the impoverished population equals approximately 30% in Peru (Hoke & Kimberly 2). This particular category of Peruvians badly needs supply programs to reduce the level of malnutrition they deal with regularly.
Peru Population = 32 ml. people.
MS= 30%*32ml=9 600 000.
Market Share
Suppose one region involves two restaurants dealing with food delivery for poor people. In that case, every restaurant serves 2% homeless individuals and about 25% marginalized people, so every restaurant spends 5% of its overall revenue.
25 regions= 50 restaurants involved in the program.
Market share = 100% ÷ number of competing businesses.
Market share of each region equals= 5%+5%=10%.
Market share of each business= 100%÷ 50 = 5000% for each restaurant.
The Average Annual Consumption
25 regions= 50 restaurants involved in the program.
(50 rest. * [sum of money every restaurant invests]) * 5% money donations= [overall sum of money]
[overall sum of money] * 12 months= [annual sum of consumption money].
The Average Selling Price
As mentioned above, restaurants do not sell anything, as it is part of charity and donations.
Market Potential
MP = N × MS × P × Q =32 000 000*9 600 000*1* [annual sum of consumption money].
Works Cited
Bedoya-Perales, Noelia S., and Glenio Piran DalMagro. Quantification of Food Losses and Waste in Peru: A Mass Flow Analysis along the Food Supply Chain. Sustainability, vol.13, no. 5, 2021, pp. 1-18.
Daneshvar, Fariborz, et al. Development of strategy for SWAT hydrologic modeling in data-scarce regions of Peru. Journal of Hydrologic Engineering, vol.26, no. 7, 2021, pp. 1-15.
Hoke, Morgan K., and Kimberly A. McCabe. Malnutrition, illness, poverty, and infant growth: A test of a syndemic hypothesis in Nuñoa, Peru. Social Science & Medicine, vol.7, no. 1, 2021, pp. 1-7.
Malerba, Daniele, Anja Gaentzsch, and Hauke Ward. Mitigating poverty: The patterns of multiple carbon tax and recycling regimes for Peru. Energy Policy, vol.149, no. 1, 2021, pp. 1-5.
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