The primary goal of this study is to explore the effects of rule networks on rule change. Organizational rules are often interdependent with other rules that govern related subtasks, workflows, actors, and organizational subunits. Therefore, rules shape the context for the use of related rules, and they can impede or intensify the change of related rules. Even though prior research has suggested that organizational rules are interdependent and can affect each other, the relationship between rule interdependence and rule change has not been systematically studied so far. This study is the first attempt to explore this relationship directly and empirically.

I focus on rule interdependencies that have been articulated and formalized as citation ties between rules. Citation ties link interdependent rules together into directed rule networks. I adopt an ego network approach and examine how shifts of characteristics of individual rules’ inbound citation networks affect their revisions.

I argue that when rules are cited by other rules, they become exposed to the experiences arising from citing rules’ contexts. Because different rules serve different roles, those experiences can be incongruous to the experiences in their own contexts. This can produce tensions, which I refer to as rule strain, for the cited rules. Rule strain produces change impulses that intensify rule revisions. Shifts in rule networks can shape the exposure of individual rules to rule strain and thereby affect their revision rates. I identified four important dimensions of exposure and developed hypotheses of their effects on rule change:​ network exposure (presence of an inbound network), exposure intensity (network size), exposure nonredundancy (network density) and exposure newness (occurrence of network change events, i.e., arrival of new ties, revisions of citing rules).

I test my hypotheses with data extracted from the archives of clinical practice guidelines (CPGs) of a Canadian regional healthcare organization, spanning the years from 1989 to 2010. I find strong evidence that rule networks affect rule change. Becoming cited by others significantly increases individual rules’ rate of revision. Moreover, I also find significant effects of network density and occurrence of network change events, but no systematic effect of network size.