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Critical realism and constructivism: merging research paradigms for a deeper qualitative study
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PurposeTraditional approaches in qualitative research have adopted one research paradigm linked to an established typology. This paper addresses the unconventional application of two research paradigms in one study. A critical realist approach was used to augment a constructivist analysis of data in a research project seeking to explore the meaning that managers in small to medium enterprises (SMEs) attach to hazard identification, the construction of a hazard profile reflective of the business and its use in assisting to manage hazards within the SME's safety management system framework. Critical realism offered a complementary but essential framework to explore causal mechanisms that led to a deeper understanding of the findings by searching for the processes and causality that lay beneath the social and organizational phenomena observed.Design/methodology/approachThis paper compares the two research paradigms in order to seek junctures and apply them to a research project. Analytical tools applied to each research paradigm within the project are presented, followed by a new multiparadigm conceptual model that integrates critical realism and constructivism, providing an original contribution of knowledge to this field of qualitative research.FindingsThe adoption of a multiparadigm model enabled not only the interpretation of social phenomena but also the determination of its causality, enabling a more insightful answering of the research question and leading to a deeper insight into the phenomenology that was studied. This research approach widens the boundaries of qualitative inquiry within organizational research by promoting strategies that challenge more traditionally anchored research typologies, and consequently contributes to better research outcomes.Research limitations/implicationsThis study was conducted across four organizations. Similar research is encouraged across a greater number of case studies to validate the process of using a constructivist and critical realist paradigm to gain a more insightful understanding of events and their causality.Practical implicationsThe comparison of two research paradigms and consequent provision of a conceptual model (Figure 3) provides potential for the development of further multiparadigm models for research projects within the field of organizational management.Social implicationsThis paper has the potential to promote engagement and collaboration between research scholars seeking to explore the use of multiple research paradigms.Originality/valueSuch an approach has not previously been widely discussed or adopted to examine qualitative data, and advances theory in qualitative research. The application of two research paradigms using such an approach can be applied to businesses in a number of different contexts to gain a more insightful understanding of research participant perspectives, observable events arising from those perspectives and their associated causality.
Title: Critical realism and constructivism: merging research paradigms for a deeper qualitative study
Description:
PurposeTraditional approaches in qualitative research have adopted one research paradigm linked to an established typology.
This paper addresses the unconventional application of two research paradigms in one study.
A critical realist approach was used to augment a constructivist analysis of data in a research project seeking to explore the meaning that managers in small to medium enterprises (SMEs) attach to hazard identification, the construction of a hazard profile reflective of the business and its use in assisting to manage hazards within the SME's safety management system framework.
Critical realism offered a complementary but essential framework to explore causal mechanisms that led to a deeper understanding of the findings by searching for the processes and causality that lay beneath the social and organizational phenomena observed.
Design/methodology/approachThis paper compares the two research paradigms in order to seek junctures and apply them to a research project.
Analytical tools applied to each research paradigm within the project are presented, followed by a new multiparadigm conceptual model that integrates critical realism and constructivism, providing an original contribution of knowledge to this field of qualitative research.
FindingsThe adoption of a multiparadigm model enabled not only the interpretation of social phenomena but also the determination of its causality, enabling a more insightful answering of the research question and leading to a deeper insight into the phenomenology that was studied.
This research approach widens the boundaries of qualitative inquiry within organizational research by promoting strategies that challenge more traditionally anchored research typologies, and consequently contributes to better research outcomes.
Research limitations/implicationsThis study was conducted across four organizations.
Similar research is encouraged across a greater number of case studies to validate the process of using a constructivist and critical realist paradigm to gain a more insightful understanding of events and their causality.
Practical implicationsThe comparison of two research paradigms and consequent provision of a conceptual model (Figure 3) provides potential for the development of further multiparadigm models for research projects within the field of organizational management.
Social implicationsThis paper has the potential to promote engagement and collaboration between research scholars seeking to explore the use of multiple research paradigms.
Originality/valueSuch an approach has not previously been widely discussed or adopted to examine qualitative data, and advances theory in qualitative research.
The application of two research paradigms using such an approach can be applied to businesses in a number of different contexts to gain a more insightful understanding of research participant perspectives, observable events arising from those perspectives and their associated causality.
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