Choosing a theme from a pool of topics is one of the hardest and important factors in a research journey. This is so because the progress & accomplishment of the study is entirely dependent on the topic that is selected.
The first step involved in this process is brainstorming. This approach is used to develop ideas and organise the thinking on a topic. This is followed by a relevance tree.
Relevance tree is a forecasting approach that identifies future requirements or objectives, then seeks to figure out the actions, circumstances, technologies, etc. A relevance tree is a strategy that subdivides a broad research theme into subtopics, thereby presenting possible ways to offer a forecast of durations and probabilities for each aspect.
When should one use this method?
Relevance tree is utilised to describe a system in-depth or evaluate situations with different levels of complexity, where each successive lower level includes subdivisions or finer distinctions. It is also used to spot problems, solutions, establish feasibility, and deduce the performance requirements of technologies, etc.
Structure of relevance tree
A relevance tree resembles the organisational chart. It describes hierarchical relationship with the help of vertical tree diagrams. The tree consists of branches at various levels. The branches at the lower level consists of a detailed and finer subcomponent of the system in comparison with that of the branches at a higher level. The point at which the branch subdivides into lower branches is called node. Each node has a minimum of two branches emerging from it. However, not all nodes are required to have the same number of branches emerging from them. In the relevance tree, each upper branch of lower branches.
Relevance numbers (numerical weight) can also be assigned to the branches of each node and can be utilised to derive relative quantitative value on the lower level of the tree. Relevance number is always normalised so that the total of the relevance number of the branches depending on a node is equal to one.
However, the meaning allocated to the relevance differs according to the purpose of the tree. The weight linked to the lowest level element is calculated by multiplying them with each path from the highest level to the lowest element objective.
Relevance tree is based on the rationales such as:
- The system can be decayed into successive complexity levels with a branch at a particular level pertaining to only one node in the above level.
- The understanding of the complex system is promoted by recognising the component and the relation of the components with one another.
A relevance tree presents information in a hierarchical form. The hierarchy starts at a higher level of branches and declines with greater degrees of detail in lower level branches. The entries at a particular level propose to explain the item to which they are attached in the above level in a detailed manner.
Typically, the entry is orthogonal at a particular level is not overlapped with any other entry, thereby being mutually different from other entries. In the last stage, the items at the identical level must be addressed from the same viewpoint. If done properly, the structure can lead to a clearer understanding of the topic under analysis.
The approach can be based on five simple steps:
- Formulation and definition of the research problem
- Identification and characterisation of factors toward solutions
- Development of a multidimensional matrix with the combination of possible solutions
- Analysis of the end-result based on feasibility of desired goals
- Evaluation of possibilities considering accessible resources
Characteristic of relevance tree
- It must be utilised for normative purpose and be viewed as a set of goals & subgoals. Each node is considered as a goal for branches depending on it.
- Branches emerging from node should be an exhaustive list. The closure of the list might be obtained by listing the elements of a finite set, if not the list must be artificially closed.
Requirement of resources
The credibility and logic of a relevance tree depend on the reliability and comprehensiveness of the contributor’s input. However, the information required will differ depending on the scale and scope of the study. For instance, for the development of a numerical relevance tree would need the utilisation of a computer to determine the relevance numbers efficiently.
Relevance tree is typically used for complex and large-scale projects. For such studies, the input from several sources is required for the development and revision of the relevance tree.
Relevance tree is proved to be a powerful stimulus to make sure that a given issue or problem is illustrated in a complete cycle and the crucial relationships among the items in consideration are presented in current as well as potential situations. It can also offer a graphical display of a complex system through which the researcher can understand the interdependencies and interrelationships among the complex variables and obtain possible solutions for the same.