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Marketing Research of American Financial Group

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Netra Shetty
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Marketing Research of American Financial Group - March 29th, 2011

American Financial Group Incorporated (NYSE: AFG) is a holding company based in Cincinnati, Ohio whose primary business is insurance and investments. American Financial Group's purpose is to enable businesses and individuals to manage risk using insurance products and services tailored to meet their specific needs.
American Financial Group's major insurance division operates as the Great American Insurance Company, founded in 1872 and focuses on property and casualty insurance services. Other affiliates and subsidiaries include American Custom, Mid Continent, National Interstate, Republic Indemnity. Additional insurance specialties include (but are not limited to) equine, trucking, executive liability, fidelity and crime, and agri-business. Great American Financial Resources is a wholly owned subsidiary of American Financial Group and supplies a range of annuities, life insurance products and supplemental insurances to individuals and enterprises.
The parent company, AFG, is owned principally by financier Carl Lindner, Jr. and his family. Carl Lindner is Chairman of the Board of Directors of AFG. The senior Lindner's sons, Carl H. Lindner, III and S. Craig Lindner serve as Co-Chief Executive Officers.
American Financial Group was ranked 486th on the Fortune 500 list in 2004. Through the years American Financial Group has owned a number of subsidiaries, real estate properties, and companies, including The Mountain View Grand Resort & Spa in Whitefield, New Hampshire, The Cincinnatian in Cincinnati, Ohio, The Biltmore in Coral Gables, Florida, Le Pavillon in New Orleans, Louisiana, and the Charleston Harbor Resort & Marina in Charleston, South Carolina. Great American Insurance Group partnered with the first professional baseball team, the Cincinnati Reds, and Hamilton County to purchase naming rights for Great American Ball Park.
On December 6, 2006, American Financial sold assets acquired from successors to the dissolution of the Penn Central Railroad including the land under Grand Central Terminal and the 156 miles (251 km) of Metro North track leading to the New York City landmark to Argent Ventures. The company announced in December 2007 that they will combine their offices and move their headquarters to the brand new Great American Insurance Building at Queen City Square in 2011.
American Financial Group was one of the first publicly traded Fortune 500 companies to make political donations after corporations' freedom of speech rights were expanded to include donations as a result of the Citizens United v. Federal Election Commission decision. Carl Linder, Jr is a longtime top Republican donor, comfortably donating millions of his personal income to candidates and political action committees,[3]which sent ripples in campaign finance circles during the 2010 mid-term elections. American Financial, of which Linder has a non-majority 42% share, donated $400,000 to the Republican-allied PAC American Crossroads[


With respect to this model, the data gathered will be assessed through the help of Microsoft excel and a statistical software called SPSS. Basically, the SPSS software will be used to validate the hypothesis. Thus, descriptive statistics, correlation and Chi-square will be run in SPSS software.

Descriptive Statistics

In the descriptive statistics, it is likely that the study will be inexpensive and swift. It can also propose unexpected hypotheses. Nevertheless, this statistics will be very firm to rule out different clarifications and principally deduce causations. This descriptive statistics utilizes observations in the study. In descriptive statistics measures of central tendency (e.g. mean, median, and mode) and measures of dispersion (e.g. standard deviation, range, variance) will be computed.



Correlation[1]

According to Guilford & Fruchter (1973), the strength of the linear association between two variables is quantified by the correlation coefficient. Since this paper is in quantitative approach which is also mainly limited to counting, coming up with frequency and cumulative distributions, and computations of percentages, then these methods of analysis yield facts and data, the uses are quite limited. Facts in and of themselves do not speech much, for instance, of achievement or performance are related to other factors that such phenomena are better understood, predicted and to some extent even controlled.

The basic purposes of sciences are description, explanation, prediction and control. Differences in a performance, for example, are better explained if other phenomena, events or even other performance are used to account for each difference. This is achieved through a process called correlation. In a sense t-tests and F-tests are special cases of correlation. Sometimes such relationship show cause-effect but sometimes it is just plain relationship.

Correlations may either be bivariate (at least) or multivariate. Actually, in this paper, the use of Pearson Product moment correlation is considered. The Pearson Product moment correlation is used if the purpose is to determine the relationship or co-variation between two variables that are usually of the interval type of data. Basically, there are two types of correlation depending on the nature of correlation. Correlation may either be positive or negative. Correlation is positive if the objects, items or cases who got high in one variable are also those who got high in another variable, and those who got low in one variable also got low in the other variable.



Data Analysis Procedures

In global integration context, there are some instances that the used were classified on the basis of intervals of time constitute vital information in the control of business activity, since this the most effective method of showing the changes that are taking place in the business, an industry or in total economic activity. Closely related to the problem of measuring changes in business activity is the making of forecast of future activity. The management of operation requires a continual making of decisions regarding the future and the basis for such forecasts is the record of the past performance.

Data on debt, sales, income, assets, economic indicators or even firm valuation are important in determining the possible future of a certain business. The said data are of interests chiefly in order that the figures for one period maybe compared with similar figures for other figures.

When observations of this kind are arranged in a time sequence and separated by (or represent) more or less regular intervals of time (months, years, decades, etc.), the progression of values is known as a time series. The concept of trend in economic time series rests in large part upon the secular growth of population, capital and resources.

In addition, it would be very helpful in the application of business cycles to business forecasting if we knew, more completely than we do the causes of the different characteristic lengths of the different industry cycles. The vast amount of study that has been devoted to the theory and behaviour of business cycles over the past 30 years has been directed mainly to the discovery of the causes of periodic behaviour of the general business cycle. These studies have been designed to show why there is a periodic movement of some regularity instead of long, slow, and random periods of increase and decrease, in other words, why a fairly regular cyclical fluctuation of business activity is superimposed on the long-term growth or decline in the level of business or why these periodic increases and decreases in activity appear to be self-generating and cumulative. Booms seem to feed on themselves and then destroy themselves.

Apparently, all these changes--trend, seasonal variation, and cycle--can be explained as fluctuations of the rate of spending. The causes of business change are as numerous and as varied as the causes of the variations of the rate of spending. Broadly considered, business cycles are caused, just as other changes in business activity are caused, by changes in the effective demand for goods and services of various kinds, by the three groups of spenders--consumers, business firms, and government bodies. At times, effective demand is so large and so persistent that capacity to business fluctuations touches the periodicity or regularity of recurring movements. For these different periodic characteristics of different industries we have no adequate and satisfactory explanation, and it is these characteristics of different periodic industry cycles which possess the most interest for the business forecaster. It is necessary, as in so many other fields of experimental, empirical knowledge, for the forecaster to use the behaviour of cycles to predict the future whether or not he fully understands the causes of the behaviour we uses. From these details of the behaviour of data, this study will consider collection of information from the staff of mobile phone service companies.

To gather pertinent data, this study will be using survey questionnaires. Particularly, the study arranges to distribute the questionnaires to the mobile phone service companies. In addition, the researcher will also consider the previous studies and contrast it to its existing data in order to give conclusions and proficient recommendations. In accordance to this, the use of IPO model will be considered to give study direction. A process is versioned as a sequence of boxes (processing elements) linked by inputs and outputs. Information or material objects flow in the course of a sequence of activities based on a set of rules or pronouncement points (Harris & Taylor, 1997). Harris & Taylor, (1997) pointed out that flow charts and process diagrams are often used to signify the process. What goes in is the input; what causes the change is the process; what comes out is the output
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Re: Marketing Research of American Financial Group
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James Cord
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Re: Marketing Research of American Financial Group - March 4th, 2016

Quote:
Originally Posted by netrashetty View Post
American Financial Group Incorporated (NYSE: AFG) is a holding company based in Cincinnati, Ohio whose primary business is insurance and investments. American Financial Group's purpose is to enable businesses and individuals to manage risk using insurance products and services tailored to meet their specific needs.
American Financial Group's major insurance division operates as the Great American Insurance Company, founded in 1872 and focuses on property and casualty insurance services. Other affiliates and subsidiaries include American Custom, Mid Continent, National Interstate, Republic Indemnity. Additional insurance specialties include (but are not limited to) equine, trucking, executive liability, fidelity and crime, and agri-business. Great American Financial Resources is a wholly owned subsidiary of American Financial Group and supplies a range of annuities, life insurance products and supplemental insurances to individuals and enterprises.
The parent company, AFG, is owned principally by financier Carl Lindner, Jr. and his family. Carl Lindner is Chairman of the Board of Directors of AFG. The senior Lindner's sons, Carl H. Lindner, III and S. Craig Lindner serve as Co-Chief Executive Officers.
American Financial Group was ranked 486th on the Fortune 500 list in 2004. Through the years American Financial Group has owned a number of subsidiaries, real estate properties, and companies, including The Mountain View Grand Resort & Spa in Whitefield, New Hampshire, The Cincinnatian in Cincinnati, Ohio, The Biltmore in Coral Gables, Florida, Le Pavillon in New Orleans, Louisiana, and the Charleston Harbor Resort & Marina in Charleston, South Carolina. Great American Insurance Group partnered with the first professional baseball team, the Cincinnati Reds, and Hamilton County to purchase naming rights for Great American Ball Park.
On December 6, 2006, American Financial sold assets acquired from successors to the dissolution of the Penn Central Railroad including the land under Grand Central Terminal and the 156 miles (251 km) of Metro North track leading to the New York City landmark to Argent Ventures. The company announced in December 2007 that they will combine their offices and move their headquarters to the brand new Great American Insurance Building at Queen City Square in 2011.
American Financial Group was one of the first publicly traded Fortune 500 companies to make political donations after corporations' freedom of speech rights were expanded to include donations as a result of the Citizens United v. Federal Election Commission decision. Carl Linder, Jr is a longtime top Republican donor, comfortably donating millions of his personal income to candidates and political action committees,[3]which sent ripples in campaign finance circles during the 2010 mid-term elections. American Financial, of which Linder has a non-majority 42% share, donated $400,000 to the Republican-allied PAC American Crossroads[


With respect to this model, the data gathered will be assessed through the help of Microsoft excel and a statistical software called SPSS. Basically, the SPSS software will be used to validate the hypothesis. Thus, descriptive statistics, correlation and Chi-square will be run in SPSS software.

Descriptive Statistics

In the descriptive statistics, it is likely that the study will be inexpensive and swift. It can also propose unexpected hypotheses. Nevertheless, this statistics will be very firm to rule out different clarifications and principally deduce causations. This descriptive statistics utilizes observations in the study. In descriptive statistics measures of central tendency (e.g. mean, median, and mode) and measures of dispersion (e.g. standard deviation, range, variance) will be computed.



Correlation[1]

According to Guilford & Fruchter (1973), the strength of the linear association between two variables is quantified by the correlation coefficient. Since this paper is in quantitative approach which is also mainly limited to counting, coming up with frequency and cumulative distributions, and computations of percentages, then these methods of analysis yield facts and data, the uses are quite limited. Facts in and of themselves do not speech much, for instance, of achievement or performance are related to other factors that such phenomena are better understood, predicted and to some extent even controlled.

The basic purposes of sciences are description, explanation, prediction and control. Differences in a performance, for example, are better explained if other phenomena, events or even other performance are used to account for each difference. This is achieved through a process called correlation. In a sense t-tests and F-tests are special cases of correlation. Sometimes such relationship show cause-effect but sometimes it is just plain relationship.

Correlations may either be bivariate (at least) or multivariate. Actually, in this paper, the use of Pearson Product moment correlation is considered. The Pearson Product moment correlation is used if the purpose is to determine the relationship or co-variation between two variables that are usually of the interval type of data. Basically, there are two types of correlation depending on the nature of correlation. Correlation may either be positive or negative. Correlation is positive if the objects, items or cases who got high in one variable are also those who got high in another variable, and those who got low in one variable also got low in the other variable.



Data Analysis Procedures

In global integration context, there are some instances that the used were classified on the basis of intervals of time constitute vital information in the control of business activity, since this the most effective method of showing the changes that are taking place in the business, an industry or in total economic activity. Closely related to the problem of measuring changes in business activity is the making of forecast of future activity. The management of operation requires a continual making of decisions regarding the future and the basis for such forecasts is the record of the past performance.

Data on debt, sales, income, assets, economic indicators or even firm valuation are important in determining the possible future of a certain business. The said data are of interests chiefly in order that the figures for one period maybe compared with similar figures for other figures.

When observations of this kind are arranged in a time sequence and separated by (or represent) more or less regular intervals of time (months, years, decades, etc.), the progression of values is known as a time series. The concept of trend in economic time series rests in large part upon the secular growth of population, capital and resources.

In addition, it would be very helpful in the application of business cycles to business forecasting if we knew, more completely than we do the causes of the different characteristic lengths of the different industry cycles. The vast amount of study that has been devoted to the theory and behaviour of business cycles over the past 30 years has been directed mainly to the discovery of the causes of periodic behaviour of the general business cycle. These studies have been designed to show why there is a periodic movement of some regularity instead of long, slow, and random periods of increase and decrease, in other words, why a fairly regular cyclical fluctuation of business activity is superimposed on the long-term growth or decline in the level of business or why these periodic increases and decreases in activity appear to be self-generating and cumulative. Booms seem to feed on themselves and then destroy themselves.

Apparently, all these changes--trend, seasonal variation, and cycle--can be explained as fluctuations of the rate of spending. The causes of business change are as numerous and as varied as the causes of the variations of the rate of spending. Broadly considered, business cycles are caused, just as other changes in business activity are caused, by changes in the effective demand for goods and services of various kinds, by the three groups of spenders--consumers, business firms, and government bodies. At times, effective demand is so large and so persistent that capacity to business fluctuations touches the periodicity or regularity of recurring movements. For these different periodic characteristics of different industries we have no adequate and satisfactory explanation, and it is these characteristics of different periodic industry cycles which possess the most interest for the business forecaster. It is necessary, as in so many other fields of experimental, empirical knowledge, for the forecaster to use the behaviour of cycles to predict the future whether or not he fully understands the causes of the behaviour we uses. From these details of the behaviour of data, this study will consider collection of information from the staff of mobile phone service companies.

To gather pertinent data, this study will be using survey questionnaires. Particularly, the study arranges to distribute the questionnaires to the mobile phone service companies. In addition, the researcher will also consider the previous studies and contrast it to its existing data in order to give conclusions and proficient recommendations. In accordance to this, the use of IPO model will be considered to give study direction. A process is versioned as a sequence of boxes (processing elements) linked by inputs and outputs. Information or material objects flow in the course of a sequence of activities based on a set of rules or pronouncement points (Harris & Taylor, 1997). Harris & Taylor, (1997) pointed out that flow charts and process diagrams are often used to signify the process. What goes in is the input; what causes the change is the process; what comes out is the output
Hey dear,

please check attachment for Annual Report on American Financial Group, so please download and check it.
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