Building a scale for dynamic learning capabilities: The role of resources, learning, competitive intent and routine patterning

Abstract

Those researching organizational capabilities have largely accepted that the most fundamental operational capabilities form a hierarchy ranging from the lower-order dynamic functional to higher-order dynamic learning capabilities. Measurability has advantaged the first two types, resulting in numerous operationalized measurement scales. Yet at the strategic level, higher-order capabilities remain unmeasured, thus perpetuating issues of causal ambiguity. This paper responds by developing and presenting a measurement scale of dynamic learning capabilities (DLCs). Using multiple sources of data, we follow a five-step process to propose to measure and then validate a reliable scale consisting of three subscales. These subscales complement and thus extend the existing exploration and exploitation learning subscales. This predictive validity is further supported by relating all our subscales to perceived performance. Employing this dedicated new scale will enhance both the validity of studies on higher-order dynamic capabilities and the understanding of how firms create and use capabilities to drive performance.