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Team members: Alexei Smirnov | Valeria Cherekaeva | Renata Abdrafikova

Introduction

McDonald’s is one of the most successful chains which offers fast food all around the world. To Russian audience, McDonald’s was introduced in 1990 and brought to Soviet people fizzy drinks, slim potato slices, and hamburgers. The popularity at that time can be explained with the novelty of the product. Today it might be explained with the habit or convenience of the service. The study by Romir (2018) showed that general attendance to the fast food restaurants increased at the end of 2018. The result of the survey showed that 72% of participants visited McDonald’s at least ones in three months, however last year the number was 67%. 

Due to the business of the citizens, food delivery companies come to the market with a service which provides to user’s opportunity to order food from a variety of restaurants, even if a restaurant does not offer delivery. Yandex.Eda is one of the most successful delivery services on the Russian market and their delivery guys can be seen everywhere in Moscow. Story of Yandex.Eda starts from 2016 when the company had a different name and different owner, in the shape as it is today company started to operate in 2018. Today Yandex.Eda in partnership with 9000 cafes and restaurants, however, Maxim Firsov, CEO Yandex Eda, mentioned that people order more often burgers, sushi, and pizza.

Research Question

In this study, we want to investigate if people order McDonald’s more often to the office or to the home. Potentially, this research can be used to understand the behavior of customers. Our hypothesis builds on the idea that office workers order McDonald’s due to the fast delivery and good customer services, however, people who order McDonald’s to home might like the taste of the product. Also, both groups might be interested in the low cost of the food. Additionally, for the project, we assumed that during the weekdays people order fast food to the office and due to the weekend days people order McDonald’s to home.

Hypothesis 1: The McDonalds in the office area will receive more orders during the working days than on weekends at lunchtime (13:00 – 15:00).

Hypothesis 2: The area with a high density of homes will have more orders during the weekends during lunchtime if to compare with working days.

Research Method

The first step of the research was to choose the office and home areas in Moscow. The data from Open Street Map was used in order to understand the number of offices, number of homes and population number around different McDonalds points. It is important to mention that before the incident with Yandex.Eda courier and while this project was in process the official webpage claimed that food can be delivered in 15 min after it cooked, however now the Yandex.Eda changed data and such information cannot be found. Nevertheless, we used Galton method to make the 15 minutes walking distance for the chosen areas.

The next step was an observation field study. During the lunch hours from 13:00 until 15:00 we counted the number of Yandex.Eda delivery guys in chosen locations. The observation took a week (from 13/05 until 19/05) in two locations.

Results and Discussion

As a result, the two McDonalds points were chosen: Lyublinskaya street, 165, building 1A (Picture 1, metro Maryino) and Presnenskaya embankment, 2 (Picture 2, Moscow City). The data suggest that Maryino does not have office buildings, however, Moscow City area has 26 office buildings. Additionally, according to Graph 1 the number of residential building is higher in Maryino area. The population number is summarised in Graph 2, and Maryino area of research has a lower number of residents if compare with Moscow City, additionally, Moscow City has 40 000 workers.

Picture 1. The McDonalds near metro Maryino in the periphery where residential houses are dominant
Picture 2. The McDonalds near Moscow City where the number of offices is higher than in other parts of Moscow

The field research took place from 13th of May until the 19th of May for the 7 days. The results are summarised in Table 1 and Graph 3. In summary, Moscow City received 1418 orders during the week, Maryino location only received 379 orders. According to the results, the highest number of orders was made on Friday (17/05) at the Moscow City area, however, the highest number of orders at the Maryino was counted on Sunday. 

Table 1. The results of the field research. The number of orders per day during lunch hours 13.00-15.00
Graph 3. The daily number of orders in Moscow City and Maryino area

The field research showed that during the weekends Marino McDonald’s restaurant full of visitors during the lunch hours if to compare it with the weekdays. Unfortunately, it was hard to make the same conclusion about Moscow City point as food court there have various restaurants and common tables so visitors are distributed around the floor.

In order to analyse the data, we still need to understand the population of each area during the office hours and during the weekends to understand a number of orders per capita. For this purpose, the additional calculation was made. We find out that the population of the houses which is in a 15 minutes walking distance in Moscow City is 27 000 plus 40 000 of office workers, in Marino 11 000 people is living in apartments, however there are no offices. According to Mosgorstats, 65% of the population can work, and 75% of this people are actually working, which means that 13 163 of people near the Moscow City are employed and 5 363 of Marino flat owners are employed as well. Therefore, 13 838 people do not work at the Moscow City area and 5 638 people have no job at the Marino point. Due to these calculations, we count the number of orders per capita which provided in Table 2.

Table 2. The number of orders per capita during working and weekend days in the Maryino and Moscow City area

According to our results, the highest number of orders per capita was at the Marino at weekends, also during the weekdays’ orders are higher than in Moscow City area. In Moscow City, McDonald’s orders are higher at weekends as well. Such results for the Marino point can be explained with observation data, as was mentioned above during the weekdays there were a few people at the restaurant, potentially not working population near the Marino point were order the food to home. A higher number of orders during the weekends can be explained with motivation spend time at home with family, it also can explain a higher number of orders at Moscow City point during the weekends. Additionally, such a trend can be explained with the fact that Marino location further from the center or entertainment locations, so local people prefer to stay at home rather than travel by metro. A low number of the orders during the working days at the Moscow City research area can be influenced by the fact that area has a variety of restaurants to order from nearby.

Conclusion and Limitations

Hypothesis 1 is wrong, the general number of orders are higher in Moscow City, however, if we look at the data per capita we see that Marino McDonalds receive more orders.

Hypothesis 2 is correct, Marino point has a higher number of orders during the weekend.

The main limitation of the research is that we were not able to provide clear information about the number of residents at the Moscow City and at the Marino point, the calculation was made by only using information from Open Street Map and analysed with Galton and Q-GIS. The next limitation is that data about the working population were calculated roughly according to statistics and may not represent a real picture.  Finally, for the researches, it was sometimes hard to calculate the number of Yandex.Eda couriers as movements were chaotic and some small miscalculations were probably made during the field research. 

If the experiment needs to be redone, we advise to include the calculation of the Delivery Club couriers to represent more realistic data about customer behavior.

References

address: 20 Myasnitskaya ulitsa
(metro stations ‘Lubyanka’ and ‘Kitay-Gorod’)
Moscow 101000 Russia

phone: +7(495)772-95-90 *15026

email: city@hse.ru