Abstract
Soft systems methodology (SSM), an analytic method commonly employed in engineering and business research, produces models focused on human activities and relevant structures used to explain complex, engineered systems. The original version of SSM involves seven stages; five address real-world aspects and observable data, while two stages leverage a systems thinking viewpoint. This approach allows the development of a simplified depiction of complex systems representative of the multi-perspective lenses used to comprehend the systemic complexity of a problem and provide a clearer picture to analysts and decision makers. This bibliometric meta-analysis of 286 relevant publications in engineering, business, and other social sciences fields explores the historic impacts of SSM on academic research and systems thinking in relevant publications that described or employed SSM for research from 1980–2018. This study produced descriptive narrative outcomes and data visualizations including information about top SSM authors, author citation impacts, common dissemination outlets for SSM work, and other relevant metrics commonly used to measure academic impact. The goal of this piece is to depict who, what, why, when, and where SSM had the greatest impact on research, systems thinking, and methodology after nearly 40 years of use, as we look towards its future as a methodological approach used to comprehend complex problem situations.
Highlights
Checkland [1] explained soft systems methodology (SSM) as an approach to understanding complex problem situations one wishes to learn more about and are poorly understood
The following sections review the relevant history of soft systems methodology and its development
Labeled General Systems Theory (GST), it was developed as both conceptual framework and mathematically expressed theory, most notably by Ludwig Von Bertalanffy [10]
Summary
Checkland [1] explained soft systems methodology (SSM) as an approach to understanding complex problem situations one wishes to learn more about and are poorly understood. There is limited research into the effectiveness of soft systems approaches over time for generating solution, in part because some analysts find the method’s requirement of stringent research that requires interactions with stakeholders and complex data sets to be onerous. This may be a misguided view because the goal of the approach is often to learn more about a situation, not generate clearly testable solutions. Such studies are reserved for future research with other, more appropriate methods to that task This piece examined the impact of SSM on academic works through a bibliometric meta-analysis of pieces that discussed as an approach or employed SSM for research. A bibliometric analysis follows, focused on publications found to discuss or employ SSM to depict the impact of the approach over the last 35 or more years
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