Reflection Post, Week 4

This week’s class discussion, readings, and film highlighted the driving force that human behavior plays in the health and sustainability of activity systems. The documentary, Boom Bust Boom, showed us that predictive patterns of behavior are a component of the analytical process of systems thinking. In looking back at the financial crisis of 2008, the behavioral patterns were there to make a prediction about the health of the mortgage and housing industries. The documentary focused on subprime lending to low income individuals as the leading cause of the financial crisis, but a recent study from the National Bureau of Economic Research offers a different story. In examining a large swath of credit data, the authors discovered that mortgage defaults during that time occurred primarily in the middle credit score range, suggesting that it was not mortgage loan defaults by low income borrowers that caused the crisis, but rather, it was real estate developers (aka, home flippers) that created a housing bubble, escalating the value of homes beyond what the market could bear. This pattern of behavior fits the narrative that speculation leads to financial crises (e.g., Dutch Tulip Mania). The documentary demonstrates the value of assessing human behavioral patterns to predict the likelihood of threats to the sustainability of an activity system.

Assessment of human behavioral patterns in systems requires looking for historical precedence. Have we seen this pattern play out before? This requires research, which is a necessary activity for analyzing human activity systems. Combining research with an understanding of the structure of systems environments yields a model that has potential predictive value. Banathy (1992) provides insight into the way a systems environment model should be structured, but my previous exposure to Engestrom’s work on activity systems (Jenlink, 2001) had me scratching my head at the boxy and hierarchical structure of Banathy’s model. Interestingly, I found his description of human activity systems almost identical to Engestrom’s version of activity theory. As shown in the image below, Banathy describes human activity systems in terms of boundaries, and input and output. The system boundary exists within a systemic environment (multiple systems), which makes up the general environment (reminding me of Habermas’ lifeworld). The movement from input to output is an iterative process that adjusts itself through feedback.

Image Source: Banathy, B. H. (1992). A systems view of education (p. 34). Englewood Cliffs, NJ: Educational Technology Publications.

Similarly, as shown in the following image, Engestrom’s activity systems framework looks at a subject-object relationship that leads to output and is shaped by the resources and boundaries (e.g., instruments, rules, division of labor) of the system. Multiple activity systems exist, and they overlap each other.

Image Source: Matbury. (2012). Illustrative diagram of Scandinavian activity network. Retrieved from https://commons.wikimedia.org

Both models describe human activity in the context of systems thinking, and both Banathy and Engestrom describe their models in similar terms. Complexity is inherent in both models, but based on the reading, I view Engestrom’s framework better at capturing the complexity of human activity systems. In Engestrom’s framework, it is easier to see where the individual fits within the context of the system, and it addresses the elements that shape the outcome of the system (rules, community, division of labor). However, the hierarchical nature of Banathy’s model shows the placement of the activity system in the larger lifeworld. Taken together, both models create a more holistic picture of human activity systems, at the same time illustrating the sheer complexity of an individual in the larger lifeworld. After all, a single individual can belong to multiple interconnected systems, and his or her behavior in one system might affect other systems as well. Similar patterns of behaviors across multiple individual systems can create a widespread ripple effect that impacts the systemic environment, such as the behaviors that led to the financial crisis of 2008.