ACKNOWLEGDEMENT Alhamdulillah‚ first of all we would like to thanks Allah SWT for giving us the opportunity to live in this world and a good health also giving us the chances to complete this assignment with flying color. This assignment was prepared for subject Principle od Entrepreneurs (ENT 530)‚ Universiti Teknologi Mara (UiTM). Secondly‚ we would like to express our deepest thanks to Madam Azita binti Aboo Bakar ‚ our lecturer for this subject ENT 530 and for guiding us for this semester 4 to
Premium Entrepreneurship Entrepreneur
Consumption in the Pizza Fast Food Industry Today‚ the average American eats 46 slices of pizza per year (about 23 pounds). Buck Jones reports "The business is only expected to grow as the industry continues to expand its product base and revenue earnings through imaginative recipes and creative marketing concepts" (Jones‚ 177). Pizza producers are searching for additional pizza products that will appeal to new markets such as the croissant‚ French bread‚ and other specialty products showing up
Premium Pizza Hut Pizza Naples
Pizza Hut: A Beginning The journey began in 1958‚ when two college students and brothers from Wichita‚ USA‚ Frank and Dan Carney‚ opened the first Pizza Hut restaurant at their hometown on June 15‚ 1958. After borrowing $600 from their mother‚ they purchased some second-hand equipment and rented a small building on a busy intersection in Wichita. The result of their entrepreneurial efforts was the first Pizza Hut restaurant‚ and the foundation for what would become the largest and most successful
Free Pizza Pizza Hut Marketing
ANALYSIS OF SICKNESS ABSENCE USING POISSON REGRESSION MODELS David A. Botwe‚ M.Sc. Biostatistics‚ Department of Medical Statistics‚ University of Ibadan Email: davebotwe@yahoo.com ABSTRACT Background: There is the need to develop a statistical model to describe the pattern of sickness absenteeism and also to predict the trend over a period of time. Objective: To develop a statistical model that adequately describes the pattern of sickness absenteeism among workers. Setting: University College
Premium Regression analysis Arithmetic mean Poisson distribution
information‚ sold information and delivery information. Management information system Input: data from TPS Processes: use the data to summarize into report. Output: the report present the employee performance‚ the time to make pizza and delivery to customers. Besides‚ report present the profit and loss. Decision support system Input: data from TPS and external data Processes: managers analyze data. Output: analyze customer’s favor and sales feature. Managers
Premium Output Sales Customer
Pizza Store Layout Simulation University of Phoenix Introduction The concept of the learning curve is a powerful tool and is applicable to all learning processes. In this simulation I became the manager and ran the Pizza store hoping to produce a better process for the amount of time a customer waits for their order. The goal of my job was to apply the learning curve concepts to test the alternative against the current process of the Pizza store. I will explain and provide information
Premium Learning curve Learning
“The Domino Effect” Teacher’s Prompt Investigate the domino effect with a set of dominoes. Aim To investigate the relationship between the mass of the dominoes‚ and how it impacts the time taken of the domino effect. Independent Variable: The mass of each domino (12.38 g‚ 32.38 g‚ 42.38 g‚ 62.38 g‚ 82.38 g). Dependent Variable: Time taken of the domino effect. Controlled Variable: The number of dominoes used (8 dominoes)‚ the distance between the dominoes (2 cm)‚ the loads used as the initial
Premium Causality Mass Force
Regression with Discrete Dependent Variable CE 601 Term Project By Classification Type of Discrete Dependent Variable Example Problems Type of Regression Model Binary 1. Consumer economics 2. Decision to vote Logistic Regression Probit Regression Ordinal 1. Opinion survey 2. Rating systems Ordered Logistic Regression Ordered Probit Regression Nominal 1. Occupation choice 2. Blood type Multinomial Logistic Regression Count 1. Consumer demand 2
Premium Regression analysis Logistic regression
NESTLE REFRIDGERATED FOODS: CONTADINA PASTA & PIZZA (A) GROUP 2 Marketing Program Design Case Analysis GROUP 2 1302-066 Keshika Lakhani 1302-070 Jubin Goel 1302-073 Keval Shah 1302-086 Mrigakshi Punga 1302-087 Nandita Jaswal 1302-093 Nirav Shah 1302-206 Gagandeep Singh NESTLE REFRIDGERATED FOODS: CONTADINA PASTA & PIZZA (A) - GROUP 2 Contents Executive Summary ................................................................................................................. 2 Q1)
Premium Marketing Product management Market research
research provides statistical analysis for gross monthly sales in 60 stores using five key measures within a 10km vicinity: number of competitors‚ population in ‘000’s‚ average population income‚ average number of cars owned by households‚ and median age of dwellings. These quantitative variables are the key determinants‚ which will provide substance for descriptive statistics and the multiple linear regression model. This research reports mainly on statistical analysis‚ providing a direct interpretation
Premium Regression analysis Statistics Standard deviation