Related diversification and unrelated diversification. Diversification is a corporate strategy to go into another business sector or industry which the business is not at present in, whilst additionally making another item for that new market. This is most risky section of the Ansoff Matrix, as the business has no involvement in the new market and does not know whether the item will be effective. Related diversification is a key change in which the organization differentiates be entering new industry yet dependably enters business in that industry at the same focus of gravity. A thankfulness for the level of relatedness is expected to gauge the measure of vital change that is being endeavored.
It’s a quantitative method that is specifically used in psychology researches and it examines whether two variables such as events, behaviuors, properties, and characteristics are casually related. In other words, it is a scientific and systematic approach to research, in which the researcher can manipulate and control the variables i,e an independent variable is manipulated and the dependent variable is measured and it could be called a true experiment. The main advantage of this method is that it allows us to determine and regulate cause and effect, and further it allows us to control the effects of extraneous variables. Experimental method involves some kind of measurement and a mathematical calculation is frequently involved. Latane and Darley used this method to examine bystanders behaviour.
Depending on “Entrepreneur”, diversification means by location, adding product service, customers and markets to company’s portfolio; it can be a risk-reduction strategy. There are three types of diversification which are concentric, horizontal and conglomerate. The following information of three types of diversification is based on startupbizhub. Firstly, concentric diversification is that existing similarities between the industries in term of the thchnological standpoint. Through this, the firm may apply and compare its technological know-how to an advantage.
ROHINI T.H 1321758 EVALUATING THE STRATEGIES OF A DIVERSIFIED COMPANIES MEANING OF DIVERSIFICATION Diversification means it is a process of adding a new line of business to the company that is different from the existing line of business operations. A diversified business company or a multi- business company is the one which is involved in two or more different line of industries, in order to attract the new line of customers and also to sustain the existing group of customers. In general when a line of business has diversified its activities, it ensures competitive advantages to such companies which allow diversification in order to minimize the risks. But it does not be the same situation all the time for all the companies, because diversification
Companies adopt either related or unrelated or both the diversifications according to their capability and need of growth. But on taking such decision on diversification,
It is commonly agreed upon to apply all methods complementary in order to gain the benefits and advantages of all methods while avoiding the disadvantages (George & Bennett, 2005: 34). There is no golden rule of how to apply the different methods and it would depend on each research. But possible scenarios could be to use a statistical analysis in order to identify relationships between variables. Followed by a case study that can provide other why those variables relate (George & Bennett, 2005: 34; Sekhon, 2004: 281). It is entirely possible to conduct an analysis the other way around.
Different approaches may have to be applied for the same individual. Comparison of learning styles should be performed on a wider variety of participants from different environments and age groups. Qualitative studies should examine the diversity of certain cognitions or behavior within a population (Jansen, 2010). Instead of using Pearson’s r correlation model, the analysis of variance (ANOVA) can be used. One-way ANOVA and two-way ANOVA analysis can be conducted, as it is able to identify significance between the means of three or more independent groups.
with more than two possible discrete outcomes. It is a With a given set of independent variables this model is used to predict the probabilities of the different possible outcomes of a categorically distributed dependent variable . Multinomial logistic regression is known by various names, such as Polytomous Logistic Regression , multiclass Logistic Regression , Softmaxregression, Multinomial logit, Maximum entropy classifier, conditional maximum entropy model. Multinomial logistic regression is used when the dependent variable in question is nominal and for which there are more than two
Therefore, covariance-based approaches are appropriate for empirical validation in well-established theories. While, PLS composes constructs from factor scores and using these scores in the following
Regression analysis is one of the most useful and the most frequently used statistical methods [6].regression analysis is a form of predictive modeling technique which investigates the relationship between a dependent and one or more predictor variables. Among the different regression models, logistic regression plays a particular role. However , the basic concept of the linear regression model is quantifying the effect of several explanatory variables on one dependent continuous variable. For situations where the dependent variable is qualitative, however, other methods have been developed. One of the method is logistic regression model, which specifically covers the case of binary or dichotomous response[8].