Research Methods

Causal Relationships

Researchers use the cause and effect framework to attain higher degrees of legitimacy in their work (Hipp, 2008). The basic principle in the causality approach is the determination of whether the trends and results in the experiment are really caused by the manipulation paradigm or whether other outside factors underlie the process. It is imperative to adopt the correct principles in the course of determining whether the general beliefs and policies correspond with the scientific results. It is because this is the surest way of validating surveys (Arpino & Aassve, 2013).

Research Objective

The two research questions introduce the audience to the variables to be studies. The first question seeks to explore the relationship between a strategic  marketing plan and business growth. Developing an effective marketing strategy to attract more people to a business is  tantamount to exploring a set of business initiatives that will work in increasing the overall market share of the business.  The second research question analyses the relationship between the success rate of the strategic marketing plan and the target market. Consequently, the study seeks to investigate the causal relationship between an effective  marketing plan and consequential business growth.

Design

Moran, Palmer & Borstorff (2007) define a true experiment design as a method where a hypothetical statement is constructed and used as the point of reference while conducting the research. The overall goal is to test all evidence against the hypothesis statement using statistical analysis. Consequently, a true experiment design is the best because groups are randomly assigned. The technique helps to ensure that no pre-existing conditions exist that will influence the variables that will contradict the results. On the other hand, in a quasi experiment design does not allow the researcher to assign random variables.

H₁  A strategic market plan creates a ripe platform where an organization can pursue growth initiatives through expanding production and increasing its market share.

The above hypothesis statement directly corresponds with the research questions because it considers all the important variables to be investigated. The aim is to measure whether it is true that an effective business plan can lead to growth and development.

Variables

The independent variable is the strategic marketing plan and the dependent variables include the market share and the  level of production. The blocking variable include the effectiveness of the marketing team to execute (execution effectiveness) and income level of the target population. The extraneous variables include the external economic conditions that could undermine consumers’ purchasing power.

Internal and External Validity

            To deal with internal validity, the research will use an error tem during statistical analysis to accommodate the blocking and extraneous variables (Moran, Palmer & Borstorff, 2007). It is because failure to consider them will lead to invalid results that are short of all the dependent variables that affect the independent variable.

            To deal with external validity, the research will carry out an ethical analysis to determine the set of moral standards that it ought to follow (Hipp, 2008). It includes furnishing the participants with all the required information that will command their voluntary consent and open disclosure.

Conclusion

            A causality experiment requires more attention because of the validity issues that surround them. The task is to determine whether the relationship really holds. This analysis evaluates a causal relationship between a strategic marketing plan and overall business growth. Care is taken to consider the extraneous and blocking variables, aside from the dependent and independent ones. To make the study valid, it is imperative to consider all the variables that affect the model, ethical considerations, and the rights of the participants as far as their involvement is concerned.

References

Arpino, B., & Aassve, A. (2013). Estimating the causal effect of fertility on economic wellbeing: Data requirements, identifying assumptions and estimation methods. Empirical Economics, 44(1), 355-385.

Hipp, J. R. (2008). Counterfactuals and causal inference: Methods and principles for social research. Contemporary Sociology, 37(4), 320-322.

Moran, F., Palmer, D. W., & Borstorff, P. C. (2007). The Relationship Between National Culture, Organizational Culture, Causal Ambiguity And Competitive Advantage In An International Setting: An Exploratory Analysis. Allied Academies International Conference.Academy for Studies in International Business.Proceedings, 7(1), 5-9.