Descriptive Research Types

TYPE OF RESEARCH:

There exists a wide range of research types, and the following paragraphs aims to describe them in relation to this study:

• Descriptive vs Analytical: Descriptive research type basically includes surveys and fact findings over a variety of types. The prime purpose of a descriptive research is to describe the state of affairs about a certain topic as it exists in present. This type of research is compatible with the term Ex-Post facto research use in Business research and social sciences. The main characteristic of this type of research is that the researcher has zero control over the variables used, i.e he can only report what has happened or what is currently happening (C.R. Kothari, 2004). Analytical research on the

In the past, this method was widely used by ethnographic researchers conducting an observation study within the participants’ atmosphere, but recently it has been widely adopted my many other social researchers. This technique is further divided into 4 categories: 1) Structured observation, which requires systematic goal setting and execution; 2) Unstructured observation, following a rather flexible approach to data collection, 3) Participant observation, which requires the researcher/observer to participate in the researched phenomena; and lastly 4) Non- participant observation, which demands the observer to stay outside the observed phenomena’s boundary and carry out a passive observation (Manohar S.Pawar, 2004). The strengths of this method is it allows the researcher to collect rich and accurate data in a natural setting, while the limitations include lack of generalizability, bias, and the inability to be deployed upon a larger group of

Bran Identity, the moderating variable in this study was measured by asking respondents to rate their psychological associations with the brand.

Structural Equation Modelling (SEM) was adopted in testing the hypothesis. Partial Least Squares (PLS) variance analysis was chosen because it is a non-parametric SEM technique and can bypass SEM’s necessity for multivariate normal data (Chin.et al, 2003). It also has the ability to model undiscovered constructs using small or medium sized samples, and this technique has been extensively used in information systems, operations management, service management, strategic management and marketing (Nambisan & Baron, 2007). Partial Least Squares method has also been held superior to traditional techniques such as analysis of variance and moderated multiple regressions while texting moderating effects (Chin.et al,