DeliverWow Case

DeliverWow are a London-based bicycle food delivery company that started business in January 2016 and is run by three brothers with an IT background. Their customer promise is that they will collect the ordered food from the producers and deliver it to the customer within 15 minutes, or else the food is free. During their first year they relied on riders recording their own delivery times. Recently they have invested in technology to monitor their riders’ performance more objectively and have fitted a random sample of 33% of their bikes with GPS trackers so that they can measure delivery times and rider speeds automatically (the other bikes were not fitted with GPS trackers). Each customer is also sent a phone text message after each delivery to ask them for their satisfaction with the delivery speed and the quality of the customer service of the rider, and the customers can gain discount vouchers for each review they provide. Due to negative media coverage of working conditions in this industry, DeliverWow have also provided each of their riders with a blood pressure monitor that they must wear during working hours. The HR Manager keeps records if blood pressure levels become unsatisfactory. 

Due to disputes within the company about the main hypotheses that should be tested, the IT director at DeliverWow has collated the data collected between March and September 2017 and asked King’s Business School to start analysis of the dataset. DeliverWow have stated that they “are interested in the statistically significant findings” that will help them “to decide on whether to keep investing in the GPS trackers or not”. 

The data provided comes from a workforce of 646 riders employed between March and September 2017 and spread very evenly across five operating regions in London. Data are provided only for riders employed continuously during this period. DeliverWow know that their riders are around 90% male, have a mean age of 20 years (SD=4.5 years) and have a mean organisational tenure of 8 months (SD=3 months). A series of interviews with some of the DeliverWow riders have also been conducted, but data from these interviews have not been provided.

The data
The following variables are included in the dataset provided:

From the first survey
• ID number [ID] – an identifying number for each rider
• London Region [region] (1=North East; 2=North West; 3=South East; 4=South West; 5=Central)
• Tracked GPS bike [GPSbike] (0 = Un-tracked GPS bike; 1 = Tracked GPS bike)
• Average delivery time [DeliveryTime] (delivery time in minutes once received from producers, rounded to the nearest minute across all deliveries made by rider)
• Late deliveries [late](1=less than 5% of deliveries > 15 minutes; 2=more than 5% of deliveries > 15 minutes)
• Customer satisfaction [CustSat](average rating on 1-7 Likert-type scale, where 1=Highly dissatisfied; 7=Highly Satisfied, rounded to the nearest integer)
• Rider Blood pressure as of September 2017 [BP](0=unsatisfactory levels; 1=satisfactory levels)



Questions to answer
Please answer the following questions in 1000 words or less. The marks available for each question give an indication of the expected word count for each question. There is no need to include the questions in your answers but make sure each answer is numbered. In your answers, cite all relevant statistics and answer the question as completely as you can (including interpretation/description of inferential statistics conducted). 

1. Answer the following:
a. Data from how many riders are contained within the SPSS dataset? 
b. What proportion of riders from each region of London has tracked GPS bikes?
c. Describe the distribution characteristics of the variable “Customer satisfaction”.
(8 marks)

2. Answer ONE of the following: Is there a dependency between EITHER a) being on a GPS tracked bike and lateness of deliveries OR b) being on a GPS tracked bike and riders’ blood pressure? 
(12 marks)

3. What is DeliverWow’s average delivery time and is this significantly lower than 15 minutes? 
(12 marks) 

4. Which t-test would tell you whether mean customer satisfaction differs for deliveries made by riders on GPS tracked bikes vs. non-tracked bikes? Perform and report this test. What assumptions would you need to make of the data for your selected test and are the assumptions satisfied in this case?
(18 marks) 

5. a) Why is statistical significance a useful concept for data analysts and b) why might a reliance on statistical significance alone be problematic for data analysts?
(15 marks)

6. To what extent would recommendations drawn from the findings here be limited, or perhaps strengthened, by methodological features of the research conducted? Support your answer fully.

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