om470

Name: ___________

Individual take-home assignment: WSJ on Queuing analysis

Please type. Submit your completed assignment on Canvas before it is due.

Instructions:

1. Read the WSJ article titled “The Science Behind Your Long Wait in Line” and answer the following questions. You can ignore the Appendix in that article.

2. Download this file and insert/type your response after each question. Do keep the original problem statements as well as everything else (e.g., header, footer, etc.). The only thing you change is to add your responses in. After you finish, upload your completed file on Canvas before the due day/time.

[Note] I will recommend you skimming through Chapter 5 as it will be helpful in answering some of the questions too. 1 point per question unless otherwise noted.

Question 1: What is queuing theory? Three key parameters of queuing theory are arrival rate, service rate (i.e., number of customers can be served within a time period) and average length (in terms of time) to pass through a queuing system. Why is queuing theory important for planning a retail operation? [This question sets the foundation for our term project.]

Question 2: What innovative techniques can retailers use to shorten waiting times or the perception of their length? Are any of those techniques commonly applicable to both online vs. in-store shopping? In answering the second question mark, be specific and give an example each that can be applied to both online and in-store shopping vs. that can only be applied to one but not the other.

Question 3: Three key parameters of queuing theory are arrival rate, service rate and average length (in terms of time) to pass through a queuing system. The article mentions that the queuing theory originated in a Danish phone company and various forms a queue can take, some are trivial like a line at an ATM, others may be serious like a list of people waiting for an organ transplant. Please specify what each of the three key parameters are in each of these three different queuing system respectively by filling in the table below. Your responses have to be context specific. To begin with, I’ve filled in the arrival rate in the phone company queuing system to demonstrate; in this context, the word “callers” is specific to the phone company context. (1pt per row; see the point breakdown in the table header)

Context of the queuing system	Arrival rate (λ) (0.3pt)	Service rate (μ): (0.3pt)	Average length in terms of time: i.e., time spent in the queuing system (W) (o.4pt)
1. phone company (you can think of this as a call center too if it helps)	Number of callers (within a period of time)
2. ATM
3. organ transplant

(OM470 W21 Chen) individual take-home assignment (WA1)