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12.1: Distinctions from Positivist Research

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    26281
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    In addition to the fundamental paradigmatic differences in ontological and epistemological assumptions discussed above, interpretive and positivist research differ in several other ways. First, interpretive research employs a theoretical sampling strategy, where study sites, respondents, or cases are selected based on theoretical considerations such as whether they fit the phenomenon being studied (e.g., sustainable practices can only be studied in organisations that have implemented sustainable practices), whether they possess certain characteristics that make them uniquely suited for the study (e.g., a study of the drivers of firm innovations should include some firms that are high innovators and some that are low innovators, in order to draw contrast between these firms), and so forth. In contrast, positivist research employs random sampling—or a variation of this technique—in which cases are chosen randomly from a population for the purpose of generalisability. Hence, convenience samples and small samples are considered acceptable in interpretive research—as long as they fit the nature and purpose of the study—but not in positivist research.

    Second, the role of the researcher receives critical attention in interpretive research. In some methods such as ethnography, action research, and participant observation, the researcher is considered part of the social phenomenon, and their specific role and involvement in the research process must be made clear during data analysis. In other methods, such as case research, the researcher must take a ’neutral’ or unbiased stance during the data collection and analysis processes, and ensure that their personal biases or preconceptions do not taint the nature of subjective inferences derived from interpretive research. In positivist research, however, the researcher is considered to be external to and independent of the research context, and is not presumed to bias the data collection and analytic procedures.

    Third, interpretive analysis is holistic and contextual, rather than being reductionist and isolationist. Interpretive interpretations tend to focus on language, signs, and meanings from the perspective of the participants involved in the social phenomenon, in contrast to statistical techniques that are employed heavily in positivist research. Rigor in interpretive research is viewed in terms of systematic and transparent approaches to data collection and analysis, rather than statistical benchmarks for construct validity or significance testing.

    Lastly, data collection and analysis can proceed simultaneously and iteratively in interpretive research. For instance, the researcher may conduct an interview and code it before proceeding to the next interview. Simultaneous analysis helps the researcher correct potential flaws in the interview protocol or adjust it to capture the phenomenon of interest better. The researcher may even change their original research question if they realise that their original research questions are unlikely to generate new or useful insights. This is a valuable—but often understated—benefit of interpretive research, and is not available in positivist research, where the research project cannot be modified or changed once the data collection has started without redoing the entire project from the start.


    This page titled 12.1: Distinctions from Positivist Research is shared under a CC BY-SA 3.0 license and was authored, remixed, and/or curated by Anol Bhattacherjee (Global Text Project) via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.