# Essays on Relationship between Delivery Time and the Selling Price Assignment

The paper 'Relationship between Delivery Time and the Selling Price" is a great example of a business assignment. Graphical and numerical summaries for the length of delivery time, the customer satisfaction factor, and the average amount gained per sale. The descriptive statistics for the variables; average delivery time, customer satisfaction and the amount gained are as shown in the table.   Delivery time Customer satisfaction Amount gained per sale Mean (μ ) 0.42 5.5 352.06 Max 0.81 10 452.00 Min 0.11 2 300.00 Variance 0.036110977 3.765306122 1415.40449 Standard Deviation 0.188118997 1.920937271 37.2437431 From the table above, the amount \$352.06/ton has a customer satisfaction mean (μ =5.5) when the product is delivered at a time (μ =0.42minutes/ton. km). It also implies that when AuCement continues to sell the 20kg bag of cement in Sydney, Canberra, Melbourne and Brisbane, it is 99 percent confident that the amount gained per sale will range between \$314.82 per ton and \$389.30 per ton.

This is based on the assumption that similar economic and geographical conditions apply equally in all the regions. Overall, the amount gained per sale is indirectly proportional to the delivery time but relates directly to customer satisfaction. Summary of frequency, the average sale price, average delivery time, and average customer satisfaction for each city The frequency table is as shown in the table below; Sale price (\$/ton) Customer satisfaction Delivery time Limits Frequency Limits Frequency Limits Frequency 300 2 2 1 0.2 7 350 26 5 26 0.5 27 400 17 8 19 0.8 14 450 4 10 4 1 2 From the table above, the selling price per ton with the highest frequency (26) was between \$300 and \$350 and followed by selling price between \$350 and \$400 with a frequency of 17.

Regarding customer satisfaction, customers who gave an average customer satisfaction score of between 2 and 5 were the highest at 26 followed by those (frequency = 19) who gave a score of between 5 and 8. On delivery time, the delivery time between 0.2 and 0.5 minutes had the highest frequency at 27 followed by customers (freq. =14) for the delivery time 0.5-0.8minutes/ton. km.

The row with the highest frequencies for the three variables is marked green in the table above. As shown in the figure above, delivery time (min/ton. km) is higher in Melbourne compared to the other three cities in Australia. This implies that it is easier to deliver the 20kg bag of cement within the shortest time in Brisbane compared to Melbourne. On customer satisfaction, as shown in the pie chart above, customer satisfaction was on average higher in Sydney (29%; μ =6.11) than Melbourne and Canberra (22%).

This could be attributed to higher delivery time which results in loss of patience among customers. From the bar chart above, the sale price (\$/ton) was higher in Brisbane (\$358.45) and Sydney (\$356.95) compared to Melbourne (\$341.64). This implies that the company could be facing huge competition in Melbourne as opposed to Sydney and Brisbane. In conclusion, the company could be less motivated in the Melbourne market because of its low selling price which could be the reason why the delivery time is high and customer satisfaction is low. Relationship between the delivery time and the selling price A simple correlation established the relationship between two variables that relate to each other.

A perfect positive correlation is indicated by +1 coefficient while a perfect negative relationship is denoted by a -1 coefficient. In this case, the correlation for delivery time and the selling price is obtained using a scatter diagram as shown below. The above scatter diagram shows that the equation is given as; Y = -87.66x + 388.4. The R2=0.196 implies that the equation of the linear line fits the data for one variable (delivery time) that explains the correlation with another variable (selling price).

The computed correlation coefficient is excel after the function; =CORREL(D2:D51,F2:F51) gives a value of -0.443. The result indicates that there is a negative correlation between the selling price and delivery time. This also means that the higher the delivery time the lower the selling price. Customers who pay more for the selling price expect the delivery time to be shorter.