A manufacturer and a retailer are evaluating to form a supply chain (i.e. to act like a single company). They are currently supplying winter gloves. The manufacturer is producing each pair of winter gloves at $3, and selling each pair to the retailer at $6. The retailer is selling to the customers at $12 per pair. The retailer is philanthropic and donates all unsold winter gloves to a nearby charity home at the end of the season. The customer demand at the retailer is uniformly distributed between 5 and 55. The retailer places only one order per season. Compute the expected profit with and without the supply chain relationship and comment if they should form such a supply chain relationship.

Taylor Smith owns a small clothing company, Cuteness for You, that offers an online subscription and personal shopping service targeted at busy families with children aged newborn to five years old. Currently, Taylor has one level of subscription service, the standard service. For $100 a month, the standard service provides its customers a monthly delivery of 10 clothing items carefully chosen to match the child's size, gender, and emerging style. The online clothing subscription market is fairly new but is growing rapidly and thus Taylor is considering extending the product line to increase its market share and profits. Taylor is debating whether to add a premium subscription service featuring profitable high-markup items for $125 per month, a basic subscription service that contains lower-markup popular items priced at $75 per month, or possibly both. Taylor knows that the new product lines provide an opportunity to attract more customers and possibly increase revenues and profit,…

A store has the following demand figures for the last four years: Year Demand 100 1 150 3 112 4 200 Given a demand forecast for year 2 of 100, a trend forecast for year 2 of 10, an alpha of 0.3, and a beta of 0.2, what is the demand forecast for year 3 using the exponential smoothing with trend method? 128 115 Ⓒ 135 Ⓒ 145

Historical demand for a product is   DEMAND January 12 February 11 March 15 April 12 May 16 June 15 Using simple linear regression analysis, calculate the regression equation for the preceding demand data. Note: Round your intercept value to 1 decimal place and slope value to 2 decimal places.   Using the regression equation in d, calculate the forecast for July. Note: Round your answer to 1 decimal place.