Strategies and Models

Picture of a telescope on an old map

Time to spend on this section: 1 hour

This section of the theme will discuss the different research strategies and models that can be used to underpin, influence and/or inform the design of a research project.

Research strategies

The decision about the use of a broadly qualitative or quantitative research strategy serves as a useful orientation on the road to performing a research project. However, you will need to make other key decisions, as well as a multitude of small managerial, logistical and/or tactical choices.

The debate (choice) between these two types of research is similar to the differences between the positivist and naturalist paradigms. Positivist researchers believe that the researcher and subject are independent, whereas the naturalist axiom believes that there is no way to separate the researcher and participant, and that people and relationships are always in a state of change. As a consequence, the choice of a qualitative or quantitative approach to research has traditionally been guided by the paradigm/subject discipline (natural or social sciences). However, this is changing, with many “applied” researchers taking a more holistic and integrated approach that combines the two traditions. This modern-day methodology reflects the multi-disciplinary nature of many contemporary research problems.

In fact, it is possible to define many different types of research strategy. The following list (adapted from Bryman and Bell, 2003) is neither exclusive nor exhaustive.

Exploratory

  • Clarifies the nature of the problem to be solved
  • Can be used to suggest or generate hypotheses
  • Includes the use of pilot studies
  • Used widely in market research

Descriptive

  • Provides general frequency data about populations or samples
  • Does not manipulate variables (e.g. as in an experiment)
  • Describes only the "who, what, when, where and how"
  • Cannot establish a causal relationship between variables
  • Associated with descriptive statistics

Analytical

  • Breaks down factors or variables involved in a concept, problem or issue
  • Often uses (or generates) models as analytical tools
  • Often uses micro/macro distinctions in analysis

Critical

  • Focuses on the analysis of bias, inconsistencies, gaps or contradictions in accounts, theories, studies or models
  • Often takes a specific theoretical perspective, (e.g. feminism; labour process theory)

Predictive/Confirmatory

  • Mainly quantitative
  • Identifies measurable variables
  • Often manipulates variables to produce measurable effects
  • Uses specific, predictive or null hypotheses
  • Dependent on accurate sampling
  • Uses statistical testing to establish causal relationships, variance between samples or predictive trends

Action

  • Associated with organisation development initiatives and interventions
  • Practitioner based, works with practitioners to help them solve their problems
  • Involves data collection, evaluation and reflection
  • Often used to review interventions and plan new ones

Applied

  • Focuses on recognised needs, solving practical problems or answering specific questions
  • Often has specific commercial objectives (e.g. product development)