Question

Passage A
In the mid-twentieth century, urban planners and traffic engineers operated under a seemingly self-evident axiom: urban traffic congestion was a symptom of inadequate physical supply, and the definitive remedy was to augment infrastructure by constructing wider, multi-lane highways. This straightforward supply-side logic dictated that carefully matching road capacity to projected peak-hour traffic volumes would ensure fluid mobility, thereby fostering economic growth and metropolitan efficiency. However, subsequent robust empirical analyses of major municipal transit networks revealed a profoundly counterintuitive phenomenon. Shortly after expansive new highway lanes were inaugurated and opened to the public, traffic congestion inevitably returned to its prior, debilitating levels. Planners had critically failed to account for "induced demand"—the behavioral economic reality that artificially lowering the time-cost of travel implicitly encourages more drivers to utilize the route, shift their preferred travel times, or abandon public transit entirely. Recognizing this dynamic required a fundamental epistemological shift within the discipline; engineers were forced to abandon static, linear supply-demand models. Instead, they had to adopt complex systems theories that treat physical infrastructure and human behavioral economics as deeply intertwined, dynamic feedback loops. The contemporary consensus now firmly rejects the notion that municipalities can simply "build their way out" of congestion.

Passage B
For decades, the standard approach to mitigating data latency and network congestion in digital communications architecture was overwhelmingly additive. Network administrators, confronting frustrating data bottlenecks and sluggish transfer rates, would routinely advocate for the deployment of thicker fiber-optic cables, upgraded routing hardware, and massively increased broadband allocation. The underlying theoretical assumption mirrored traditional civil engineering: network congestion was simply a physical constraint problem waiting to be solved through brute-force expansion. Yet, time and again, the activation of vastly expanded network capacities did not yield the promised long-term relief in data transmission speeds. Instead, the sheer availability of broader bandwidth immediately catalyzed the development and widespread adoption of increasingly data-intensive applications—such as continuous high-definition video streaming, constant background syncing, and distributed cloud-based processing—which quickly consumed the newly available capacity. This phenomenon, effectively an instance of "induced data consumption," demonstrated that digital network traffic is rarely a fixed, predictable quantity awaiting sufficient pipes. Rather, it acts as a highly elastic variable that rapidly expands to fill whatever structural capacity is provisioned for it. Consequently, modern network architecture has largely pivoted away from the futile cycle of pure capacity expansion. The discipline now focuses primarily on sophisticated traffic shaping algorithms, intelligent packet prioritization, and proactive demand-management protocols.

Question:
The authors of both Passage A and Passage B develop their central arguments by employing a parallel sequence of rhetorical and logical steps. Arrange the following structural elements in the exact order in which they appear in BOTH passages to advance their respective critiques.