Case Study Review "Simulation Case Study: Phoenix Boutique Hotel Group", business and finance homework help

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Review "Simulation Case Study: Phoenix Boutique Hotel Group" (ATTACHED)for this topic's case study, in which you provide guidance to Phoenix Boutique Hotel Group (PBHG) founder Bree Bristowe.

In addition to creating a simulation model, prepare a 500-750-word recommendation for Bristowe's best course of action. Explain your model and the rationale for your recommendations.

Use Attached Excel spreadsheet file for the calculations and explanations. Cells should contain the formulas (i.e., if a formula was used to calculate the entry in that cell). Students are highly encouraged to use the "Simulation Case Study: Phoenix Boutique Hotel Group Template" Excel resource to complete this assignment.DONOT MODIFY EXCEL TEMPATE TEMPLATE,add numbers and formulas to given template

Must follow APA styling,Rubric attached-,all sections under Rubric must be answerd

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Simulation Case Study: Phoenix Boutique Hotel Group Phoenix Boutique Hotel Group (PBHG) was founded in 2007 by Bree Bristowe. Having worked for several luxury resorts, Bristowe decided to pursue her dream of owning and operating a boutique hotel. Her hotel, which she called PHX, was located in an area that included several high-end resorts and business hotels. PHX filled a niche market for “modern travelers looking for excellent service and contemporary design without the frills.” Since opening PHX, Bristowe has invested, purchased, or renovated three other small hotels in the Phoenix metropolitan area: Canyon Inn PHX, PHX B&B, and The PHX Bungalows. One of the customer service enhancements Bristowe has implemented is a centralized, toll-free reservation system. Although many customers book specific hotels online, the phone reservation system enables PBHG to find the best reservation match at all properties. It has been an excellent option for those customers who have preferences regarding the type of room, amenity options, and the best price across the four hotel locations. Currently, three agents are on staff for the 6 a.m. to 2 p.m. call shift. The time between calls during this shift is represented in Table 1. The time to process reservation requests during this shift is in Table 2. Table 1: Incoming Call Distribution Time Between Calls (Minutes) 1 2 3 4 5 6 Probability 0.13 0.23 0.27 0.19 0.15 0.09 Table 2: Service Time Distribution Time to Process Customer Inquiries (Minutes) 1 2 3 4 5 6 7 Probability 0.19 0.17 0.16 0.15 0.11 0.08 0.03 © 2017. Grand Canyon University. All Rights Reserved. Bristowe wants to ensure customers are not on hold for longer than 2 minutes. She is debating hiring additional staff for this shift based on the available data. Additionally, Bristowe and PBHG will soon be featured in a national travel magazine with a circulation of over a million subscriptions. Bristowe is worried that the current operators may not be able to handle the increase in reservations. The projected increase for call distribution is represented in Table 3. Table 3: Incoming Call Distribution Time Between Calls (Minutes) 1 2 3 4 5 6 Probability 0.26 0.27 0.24 0.14 0.11 0.06 Bristowe has asked for your advice in evaluating the current phone reservation system. Create a simulation model to investigate her concerns. Make recommendations about the reservation agents. 2 Arrival Interval Distribution Random Number Lower Limit Probability 0,13 0 0,23 11 0,27 32 0,19 54 0,15 74 0,09 90 Service Time Distribution Random Number Lower Limit Probability 0,19 0 0,17 20 0,16 39 0,15 57 0,11 74 0,08 87 0,03 97 Customer Number 1 2 3 4 5 6 7 8 9 10 11 12 Random Number 70 79 32 68 90 98 72 37 17 6 34 97 Range Upper Limit Arrival Gap Minute 10 31 53 73 89 99 1 2 3 4 5 6 Range Upper Limit Service Time (minutes) 19 38 56 73 86 96 99 1 2 3 4 5 6 7 Arrival Gap Random Number 15 73 44 83 30 15 61 66 23 27 28 68 Service Time Arrive Time Summary for This Trial Run max 13 14 15 96 4 37 82 39 46 Service Start Service End Time in System Summary for This Trial Run Average: maximums Time on Hold Time Server Idle Percent Utilization
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Simulation Case Study: Phoenix Boutique Hotel Group
[Student Name]
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Table of Contents
Simulating the current scenario ................................................................................................. 5
The information in gave for the situation focuses towards an utilization of lining hypothesis
with 3 servers, a mean landing and a mean administration rate; both in view of likelihood.
Since, the entry in the present framework is arbitrary; the Poisson appropriation has been
considered for examination. ....................................................................................................... 5
The landing and administration rates ..................................................................................... 5
With a specific end goal to accept a solitary landing and administration rate for the mining
model, a weighted normal has been taken. These counts add up to mean landing time hole of
3.45 minutes and a mean administration time of 2.85 minutes. To compute the rates,
reciprocals of these figured weighted means was utilized. ........................................................ 5
The likelihood of zero clients ................................................................................................ 5
To effectively apply Poisson dispersion for figuring the holding time and sit out of gear time,
it is essential to know the likelihood of "No" client in the framework. This has been
ascertained utilizing the "P0inf" work, which evaluates the likelihood for P (x = 0) for a
Poisson Distribution. .................................................................................................................. 5
Results of the present framework .......................................................................................... 5
In view of the sources of info given, the normal use of the servers is 46.3% with a most
extreme of 100%. The reproduction comes about all the time bring up that the normal use of
the server is between 35 to half, though the most extreme usage extends between 80...


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