یک رویکرد چند سطحی به ایجاد و رهبری سازمانهای یادگیرنده

A multilevel model is offered proposing that organizational learning is an interdependent system where effective leaders enact intervention strategies at the individual (micro), network (meso), and systems (macro) levels. We suggest that leaders approach organizational learning by setting the conditions and structure for learning to occur, while limiting direct interference in the actual creative processes. First, leaders may increase the level of developmental readiness of individual followers, thereby increasing their motivation and ability to approach learning experiences and adapt their mental models. These individuals then serve as catalysts of learning within and between social networks. Second, leaders may promote the diffusion of knowledge between these knowledge catalysts within and across social networks through influencing both the structure and functioning of knowledge networks. Finally, leaders may target actions at the systems level to improve the diffusion to, and institutionalization of, knowledge to the larger organization.

Organizational learning and adaptation is inherently complex in that it involves the conjunction of networks of varied and often conflicting individuals, groups, functions, policies, and processes. Through these competing demands, ideas emerge and increase in complexity (Uhl-Bien, Marion, & McKelvey, 2007). The literature suggests that leaders can approach a complex context either with a reductionist strategy aimed at attempting to retain positive control over what is being learned, or by absorption via focusing on adaptability (Marion & Uhl-Bien, 2001). The leadership literature has largely viewed organizational learning and adaptation through reduction, suggesting that top-down and particularly linear learning processes can be initiated and controlled by senior leaders (Beckhard and Harris, 1977 and Van de Ven and Poole, 1995). Conversely, based on recent theories of complexity leadership, we suggest that social systems in complex organizational contexts are inherently unstable and unpredictable, and the causal effects of leadership on organizational outcomes are rarely directly observable or entirely deterministic (Hannah et al., 2008 and Marion and Uhl-Bien, 2001). In sum, a complex context characterized by dynamic and discontinuous forces prevents the management of organizational learning entirely through top-down processes (Bridges, 1986 and Weick and Quinn, 1999). The challenge for leaders, then, becomes how to pursue an absorption strategy that builds organizational capacity for learning and adaptability across organizational levels.

The foremost implication of this framework is that leading organizational learning is a multilevel and multistage process requiring an integrated micro (individual), meso (network), and macro (systems) approach to the actions of leaders. Our position is that the process is best affected when a system of formal and informal leaders (i.e. leadership): 1) foster follower developmental readiness at the individual level and promote their learning through engagement in developmental experiences, 2) facilitate effective knowledge networks for these key knowledge catalysts to operate within and between, and 3) scan, sanction, and institutionalize critical emergent knowledge at the systems level using both leadership and management practices. Together these actions promote absorption of internal and external complexity and ongoing adaptive learning. Our model holds that individuals are the fulcrum of organizational learning and require developmental readiness to learn. Achieving organizational learning, however, requires diffusion of knowledge sponsored by highly effective learning networks. Individual and network approaches are thus each necessary, yet not sufficient without the other. We have also argued for both a top-down and bottom-up approach to leadership where leaders set the conditions and structure for knowledge creation and emergence, allow the creative process to self-organize, and later reinforce diffusion and crystallization. Some boundaries of our model should be noted. First, although we argue leaders can influence the conditions for knowledge to emerge, we know that leader influence is restrained as social networks are partially self-organizing. Indeed, complexity theory informs us that the emergent products of human interactions are dynamic and difficult to predict (Marion & Uhl-Bien, 2001). Reinforcing our call for loose-tight leadership, we propose that too extensive of an intrusion of leadership into the dynamic of social networks can be counter-productive. Further, this model assumes organization members have ample access to information that then serves to initiate the knowledge process. The proposed model would likely be ineffective in organizations that silo or horde information for purposes of control. Finally, we are aware that the attributes of the new knowledge itself (e.g. its complexity or intangibility) will influence the rate of its diffusion and adoption (Rogers, 2003), and that these attributes may require different leadership interventions. We suggest that the testing of this model might begin with assessing the levels of developmental readiness (e.g., metacognitive ability, goal orientation, and learning efficacy) of members in a sample of social networks and subsequently assess how networks with members of greater versus lesser readiness create and diffuse knowledge. Further refinement could be made by assessing network structure and functioning. Controlling for developmental readiness, researchers might assess how the aspects of network structure (e.g. density), functioning (e.g. team LMX), and leader behaviors (e.g., vision, loose-tight, and so forth) may influence the creation and diffusion of knowledge. Additionally, initial research could assess the positions (nodes) and centrality of highly developed knowledge catalysts in their given social networks to determine the manner in which they serve to diffuse knowledge within and serve as gatekeepers between social networks by creating bridging ties. Further, although it has been conducted computationally through simulation (e.g. Fang et al., 2008 and March, 1991), researchers in a field setting might observe the performance of semi-autonomous clusters versus more homophilous structures in the creation and diffusion of knowledge. In summary, by focusing on establishing the conditions for individual learning and the diffusion of mental models across social networks and systems, we believe that leaders can create a true, veritable learning organization where learning is not something the organization merely does, but is inculcated into the climate and culture and reinforced throughout social networks as a way of being. This requires not only powerful individuals at the top of the organization, but perhaps more importantly, powerful, empowered formal and informal leaders who are capable and willing to intervene across levels for the purpose of learning.