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Case Synopsis (include a brief summary of the case and the business issue(s)being studied)



“The fastest growing sector of the electric vehicle economy in America isn’t a part of Tesla, isn't the new electric Ford Mustang, nor is it any of the new electric car brands you’ve never heard of... Surprisingly, it’s electric bikes. E-bikes as they’re now called are outselling their four-wheel counterparts 2:1. In fact, eBikes sold over 500,000 units in America in 2021 and are expected to gain 13% by the end of 2022.” ABC News (August 26, 2022)


GoTrax produces electric bikes (e-bikes) designed for the urban riders looking for a high-performance low-cost alternative to driving a car. For the past ten years, GoTrax outsourced their manufacturing process to a manufacturer in Taiwan. Despite the global supply chain that GoTrax has developed, they are considering if they should vertically integrate into manufacturing and produce the e-bikes themselves.

In the e-bike industry, most manufacturing has been taking place in Asian countries, where there is significant low-cost labor available to produce the products. As a result, GoTrax is considering setting up their own in-house production facility in Nepal. However, they are not ruling out the option to continue to outsource manufacturing (in Taiwan).

Given their current supplier in Taiwan, they would not need to pay any fixed cost but would have to guarantee to purchase 55K units for $1100 each.


If they decided to produce the e-bikes themselves in Nepal, they would have an estimated fixed cost of approximately $21 million dollars including mortgage, machinery, overhead and fixed labor costs. The unit cost to manufacture each e-bike would be $825.


The selling price of the GoTrax e-bikes would be $1895 each. One of their main concerns is regarding demand. If demand is strong, the number of e-bikes they can sell is uniformly distributed between 45K and 75K. If demand is weak, the number of e-bikes they can sell is uniformly distributed between 20K and 50K.  There is a 60% chance that demand will be strong.


If GoTrax chooses to continue to outsource and the demand is greater than the 55K, they can only sell the 55K e-bikes that they purchased. If demand is less than the 55K e-bikes, they will only earn revenue on the amount demanded even though they must purchase the full 55K e-bikes from their vendor.


If GoTrax chooses to manufacture the e-bikes themselves, they can produce an initial 30K e-bikes and then will have the option to run a second production run of anywhere between 0 and 45K additional e-bikes in response to market conditions. The timing of the second production run would be shortly after GoTrax learns if the market will be weak or strong. Thus, the total quantity that GoTrax can produce will vary between 30K and 75K e-bikes – that’s a 30K minimum from the first production run plus anywhere from 0 to 45K units for the second run.


ce again, given that demand varies, if GoTrax produces more e-bikes than the demand, it will only be able to collect revenue from the e-bikes sold and if the demand is greater than the number of e- bikes produced (after the second production run), GoTrax can only sell the number of e-bikes produced.




Use this information, to advise GoTrax on their decision. Prepare an Executive Summary report (approximately 1 to 2 pages (plus appendices) and include the following sections) that summarizes your findings and recommendations.  Be sure to include the following in your report:

1. (10 points) Case Synopsis (include a brief summary of the case and the business issue(s)being studied)


2. (50 points) Methodology (including a discussion of what information was provided and how you used this information to analyze the problem)

(a) Organize the available data on cost, revenue, and probability estimates in a table.

(b) Set up a decision tree to model the scenario presented to GoTrax. I want to see two versions of your decision tree.

i. First, show the tree with the algebraic formulations as your payoffs before you run the simulations – see the examples in the lecture notes (eg. from FOOZ lecture example

= $250*MIN(D, Q) - $150000 - $130Q)

ii. Second (completed after step (c)), after running simulations and optimization, show the decision tree with your payoffs (average profit calculated from the four simulations). Show your solved decision tree.

(c) Use simulation to estimate the expected profit generated for each option under both weak and strong demand scenarios. HINT: for the simulations, use 500 samples each. You will have four worksheets with simulations – OUTSOURCE-WEAK; OUTSOURCE-STRONG; MANUFACTURE-WEAK; MANUFACTURE-STRONG)

For the manufacturing option, use Optimization to calculate the optimal number of e-bikes to produce for both the weak and strong demand scenarios.



(1) You may either draw out the decision trees using the drawing tools in Word/PPT or you may use SilverDecisions. Be sure to differentiate between Decision Nodes and Chance (event) nodes and label all branches.

(2) Each of your simulations should be on separate Excel worksheets. All worksheets should be in one Excel file with clearly labeled tabs. To generate your simulations, use the Random Number Generator (instead of the RAND() function). Please use the last four numbers of one of the team members CWID as your random seed. Please indicate the random seed and which team member CWID was used in both the comments for submission and in your write-up.


3. (20 points) Findings and Conclusions (include summary of analysis results) Based on your analysis, respond to the following:


(a) Provide a recommendation for GoTrax including their decision to continue to outsource or vertically integrate the manufacturing. Included the expected return/cost for the decision based on your decision tree (and simulation and optimization values).

(b) SENSITIVITY ANALYSIS (Note: for each of these scenarios, you only need to show your revised solved decision trees – see (ii) above – or summarize the revised expected values in a Payoff Table.

a. Scenario 1: As cities and states are developing more legislation regarding the use of e-bikes, the demand for e-bikes may decrease and the likelihood of a strong market may be reduced to 30%, would this change your decision to OUTSOURCE or MANUFACTURE? If so, how?

b. Scenario 2: On the other hand, with continued increases in car prices, gasoline, and an overall return to the office, the demand for e-bikes may continue to soar despite and regulations making the likelihood of a strong market 90%. Would this change your decision to OUTSOURCE or MANUFACTURE? If so, how?


4. (20 points) Recommendations. For your management perspective, what other factors (not included in the model) need to be considered in making the recommendations? Do you agree with the decisions from your quantitative analysis?  Why or why not?

You could include a concise summary based on research on current trends with demand for e- bikes.



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