Index Cover Page 1 1. Executive Summary 3 2. Background 3 3. Issue Statement 4 4. Analysis of the problem 4-9 1. Moving Average 4-6 2. Holt Winters’ Exponential Smothing 6-7 3. Simple Average 7 3. Exponential Smothing 8-9 5. Recommandations 10 6. References 11 Executive Summary In the given case study, Snow the revenue manager of the Hamilton hotel has to make a decision which is to accept the group of not for 22nd August. As it is a business hotel and generally it
Orwa Akuno1 Charles Wambugu Mwangi2 Lawrence Areba Bichanga3 Michael Oduor Otieno4 Department of Mathematics, Egerton University, Egerton Kenya. Abstract In this paper, an attempt has been made to forecast tourists’ arrival using statistical time series modeling techniques-Double Exponential Smoothing and the Auto-Regressive Integrated Moving Average (ARIMA). It is common knowledge that forecasting is very important in making future decisions such as ordering replenishment for an inventory system
PART A: QUESTION 1: Low wage rates is one of the advantages international companies enjoy when they decide to produce in a particular location. The advantage arise due to the difference currency rate between countries. A close example would be Malaysia and Singapore. Every $ 1 of Singapore equals to RM 2.6 of Malaysia. Malaysia is a developing country. Low wage is Malaysia and other countries similar to Malaysia is just the impact of global capitalism. Companies that choose to pay low wages by