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The task is to undertake a simulation (role-play) of the business decision-making process. This simulation is to be completed and submitted individually, however students may

The task is to undertake a simulation (role-play) of the business decision-making process. This simulation is to be completed and submitted individually, however students may collaborate on some parts of the simulation.

For the simulation, you will play the role of CEO of 'Smart Ride', a new ride sharing company (of the likes of Uber, DiDi, Ola, etc.) that is about to enter the market. The market currently consists of two firms with roughly equal market share - 'Mega' and 'Sprite'. Your task is to answer the questions below.

  1. Due to a system glitch, prices were randomly varied in the ride sharing industry throughout the previous financial year. A data analyst compiled the different prices and number of rides requested in the dataset "ride_share_demand Download ride_share_demand". Note that each row in this dataset corresponds to a day of the year, with 365 rows (days) in total. Use this dataset to plot the prices and ride sharing requests across the year. Comment on the correlation between these two series.
  2. Now use this dataset to draw a demand curve for the industry.
  3. The data analyst included a flag for if the price and number of requests was observed on a Friday or Saturday. In the dataset this information is recorded in the column "Friday or Saturday" which is equal to 1 if the day is Friday or Saturday, and is equal to zero for all other days of the week. Without looking at the data, do you expect demand to be higher on these days than other days? Write down your prediction and explain why. Then test your prediction with the data. What do you conclude?
  4. Smart Ride's data analysts have determined that its marginal cost curve is given by the equation MC = 0.0000004*Q where Q = kilometres driven. Smart Ride's competitors currently charge consumers an average flat rate of $0.5 per kilometre driven. Assume that the ride share market is perfectly competitive. Draw Smart Ride's marginal revenue and marginal cost curves in a single diagram (it does not need to be to scale). Then calculate the optimal number of kilometres driven by Smart Ride's fleet if it is profit maximising. Given your answer to (3), do you think it makes sense that there is a single flat price on every day of the week? If not, what would you propose instead? Next, discuss whether it is reasonable to assume that the ride sharing market is perfectly competitive. If not, what type of competition do you think best describes this market (explain why)?
  5. Although initially Smart Ride attracted many customers, after six months of operations, under heavy competition, it has been forced to lower its price to its break-even point to stay in the industry. Work with another colleague in this subject (or a set of colleagues, but not more than five) to brainstorm strategies Smart Ride could use to improve its market share and profitability. Write down the strategies your team came up with, distinguishing between 'demand side' and 'supply side' strategies. There is no limit to the number of strategies you can propose, but you should propose at least four. Provide the names of your group members with your answer.
  6. Again working with your group, go through each strategy and discuss its pros and cons. Include the results of these discussions in your report.
  7. For feasibility, Smart Ride can only implement one strategy at this time. Choose one strategy that your group came up with that you think is the best option and justify your selection. You should work alone on this question.
  8. Finally, create an evaluation plan for your chosen strategy. The evaluation plan will set out how you will determine whether your strategy was successful or not. It should include details on how you will implement your strategy (e.g. market wide, with a test market etc.), a timeline, the key data you plan to collect, and how you plan to analyse these data.

Criteria

  • A range of visualization techniques are utilized to analyse the trends within the data
  • The causal relationship among key variables is identified and interpreted
  • The development of the specified events is predicted effectively
  • Results are presented clearly and unambiguously to a professional audience using an appropriate medium

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