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Visualization of causation in social-ecological systems

PublikationArtikel (med peer review)
Karl Wennberg

Sammanfattning

In social-ecological systems (SES), where social and ecological processes are intertwined, phenomena are usually complex and involve multiple interdependent causes. Figuring out causal relationships is thus challenging but needed to better understand and then affect or manage such systems. One important and widely used tool to identify and communicate causal relationships is visualization. Here, we present several common visualization types: diagrams of objects and arrows, X-Y plots, and X-Y-Z plots, and discuss them in view of the particular challenges of visualizing causation in complex systems such as SES. We use a simple demonstration model to create and compare exemplary visualizations and add more elaborate examples from the literature. This highlights implicit strengths and limitations of widely used visualization types and facilitates adequate choices when visualizing causation in SES. Thereupon, we recommend further suitable ways to account for complex causation, such as figures with multiple panels, or merging different visualization types in one figure. This provides caveats against oversimplifications. Yet, any single figure can rarely capture all relevant causal relationships in an SES. We therefore need to focus on specific questions, phenomena, or subsystems, and often also on specific causes and effects that shall be visualized. Our recommendations allow for selecting and combining visualizations such that they complement each other, support comprehensive understanding, and do justice to the existing complexity in SES. This lets visualizations realize their potential and play an important role in identifying and communicating causation.

Banitz, T., Hertz, T., Johansson, L. G., Lindkvist, E., Martinez Pena, R., Radosavljevic, S., … & Grimm, V. (2022). Visualization of causation in social-ecological systems. Ecology & society, 27(1).


Liknande innehåll

Fooled by diversity? When diversity initiatives exacerbate rather than mitigate inequality
Artikel (med peer review)Publikation
Hellerstedt, K., Uman, T., & Wennberg, K.
Publiceringsår

2022

Publicerat i

Hellerstedt, K., Uman, T., & Wennberg, K. (2022). Fooled by diversity? When diversity initiatives exacerbate rather than mitigate inequality. Academy of Management Perspectives.

Sammanfattning

This article analyzes and critically discusses the business case logic of Diversity, Equity, and Inclusion (DEI) initiatives. We highlight the value-in diversity logic for organizations and compare this with both the recent logic of power activism driven by internal and external lobbying and the classical moral justice logic originating in the civil rights movement,showing how the concepts of diversity, equity, and inclusion are seen differently in research and advocacy as organizational inputs, sought-for outputs, or as a context for social change…

Crises, Covid-19, and Entrepreneurship
Artikel (med peer review)Publikation
Batjargal, B., Jack, S., Mickiewicz, T., Stam, E., Stam, W., & Wennberg, K.
Publiceringsår

2023

Publicerat i

Entrepreneurship Theory and Practice.

Sammanfattning

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The article can be accessed here.

Evaluating Evaluations of Innovation Policy: Exploring Reliability, Methods, and Conflicts of Interest
BokkapitelPublikation
Collin, E., Sandström, C., & Wennberg, K.
Publiceringsår

2022

Publicerat i

Questioning the Entrepreneurial State, 157.

Sammanfattning

Expansions of innovation policies have been paralleled with an increase in the evaluations of such policies. Yet, there are few systematic evaluations of how such evaluations are conducted, by whom, and their overall conclusions. We analyze 110 evaluations of innovation policy in Sweden from 2005 to 2019. Our findings show that the majority of these evaluations are positive, about one-third are neutral in their conclusions, and very few are negative. The majority of evaluations were conducted by consulting firms, close to one-third by expert government agencies, and around 10% by university researchers or as self-evaluations by the governmental agencies responsible for the policy themselves. Few evaluations employed causal methods to assess the potential effects of policies. We discuss conflicts of interest and question the reliability of evaluations of innovation policy.

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