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Organizational Learning (OL) is a scientific field characterized by a long history and growing interest, so to be considered a core and promising concept in theory and practice related to the management and the organization of work. This addresses the two main issues that have been dominating scientific debate in the area: the terminological confusion and the paucity and limitedness of the relevant empirical studies. The perceived need for systematization is not just a call for a unified vocabulary, but mainly a call for epistemological advances on topics like knowledge, learning, organizations, and innovation. These problems may be generalized to the claim that the social sciences are strong on theory, but relatively weak on practice, and that organizational learning appears to be no exception. The aim of this is to discuss some theoretical proposals on those topics, casting them within the complex systems framework, and to outline empirical research relevant to the issues discussed. Keywords: organizational learning, knowledge, complex systems, innovation. Introduction There is a long history to the study of organizational learning and interest in it is still growing (Visser 2017). In recent years, however, terminological issues have been crucial to the field. While organizational learning has been widely considered as a source of strategic advantages (Maula 2017), the phrase organizational learning has been used and conceptualized in a confusing variety of interpretations (Garavan 1997, Huysman 2017) and little consensus has been achieved on its precise meaning (Thatchenkary 1996). According to Clegg, Kornberger and Rhodes (2017) this not only requires a unified vocabulary but hints above all at the need for a deeper understanding of topics like knowledge, learning, enterprises and innovation. The current addresses these issues and proposes epistemological advances cast within the theoretical framework of complex systems (von Bertalanffy 1967), a framework which is consistent with what is currently known about both human biology and the structure of organizations (Magalhaes and Sanchez 2017). Complex systems theory provides a basis to understanding the wide array and many types of macrolevel phenomena that will arise when individuals are brought together and begin to act in coordinated ways (Goldspink and Kay 2017). We will outline a number of universally accepted features of complex systems that characterize the domain (Heylighen 2017) and discuss their implications for the world of organizations. Volume I, Issue 1, 2017 6 Like all complex systems, organizations will not fit into linear models and the idea of causal predictions which is embedded into them. However, there may be certain long-term patterns underlying the behaviour of complex systems, and it may still be possible to formulate some simple general rules that describe complex systems behaviour (Jackson, 2017). The relations between knowledge processes and innovation Organizational knowledge is widely recognized to play a key role in the creation of innovation (Davenport and Prusak 1998, Drucker 1999, Nonaka and Takeuchi 1995, Stata 1989), so much so that De Geus (1988) claimed that the ability to learn faster represents a company's only sustainable competitive advantage. More generally, the evidence is compelling of a connection between an organization's human resources management and its performance (see Wright, Gardner, Moynihan and Allen 2017 for a review). However, the models that have been proposed to capture this relation often are unclear as to what exactly leads to what (Alcazar, Fernandez and Gardey 2017, Gerhart 2017). Katou and Budhwar (2017) ascribe this limitation to the use of inappropriate statistical methods: most studies, they argue, have been based on cross-sectional data, employing either hierarchical regression models or competing regression models, without proving causality. While the importance of methodology is undeniable, however, we believe that the problem of proving causality goes beyond it, and that a further theoretical analysis of the very nature of the relations that hold between HRM practices and firm performance is needed. According to Baker and Sinkula (2017), differences in learning orientation may yield differences in innovation. It has also been suggested (Day 1994, Slater and Narver 1995, Dickson 1996, Han, Kim and Srivastava 1998, Baker and Sinkula 1999a, 1999b) that the ability to engage in higher-order learning, combined with a strong market orientation, makes a company more likely to achieve long-term competitive advantage in dynamic markets. Of course, it would be factitious to look for linear causation when studying a relation which appears to be circular and complex. A virtuous circle may instead be envisaged whereby well-framed HRM practices impact positively on firm performance, making further investments in human resources themselves possible; of course, a specular vicious circle may be envisaged as well, going the other way round (Dougherty 1992). On the one hand, organizations that depend on innovation to survive need to continuously improve how they deal with and learn from any new and unfolding innovation journey (Van de Ven, Polley, Grau and Venkataraman 1999). On the other hand, highly innovative companies often find it necessary to invest in training, since the specialized skills that they need are not easily recruited (Garud et al. 2017). Finally, there can be little doubt that the whole picture would include internal factors that are not strictly knowledge-based, like corporate climate, as well as broader socio-economic ones (Purcell, Purcell and Tailby 2017). Therefore, time becomes the key factor to capture the actual causal dynamics; it should be taken into account with longitudinal studies (Katou and Budhwar 2017). Given this landscape, it is unsurprising that organizational learning has become a core and promising notion in theories and practice related to the management and organization of work (Clegg, Kornberger and Rhodes 2017). However, the ways in which such phrase is used and conceptualized appear to be confusing (Garavan 1997, Huysman 2017): little consensus has been reached on its precise meaning (Thatchenkary 1996) beyond accepting that if we talk about knowledge and learning in organizations, then we are referring to organizational learning Skerlavaj and Dimovski (2017) as many as fourteen different definitions of organizational learning, ranging from a focus on problem solving and recovering (e.g. Argyris and Schön 1996: organizational learning is a process of detecting and correcting errors) to a focus on innovation (e.g. Stata 1989: organizational learning is the principal process by which innovation occurs), from an informationprocessing view (Huber 1991: an organization learns if through its processing of information the range of its potential behaviours is changed) to a semiotic or phenomenological one (Schwandt and Marquardt 2017: organizational learning represents a complex interrelationship between people, their actions, symbols, and processes within the organization), and so on. Such proliferation of definitions can, at least to some extent, be seen as a natural side effect of the great and growing interest in a lively and important field of research and practice. As a sign of a still increasing amount of interest, Visser (2017) lists several special journal issues devoted to the topic: one of Organization Science in 1991, one of Accounting, Management and Information Technology in 1995, one of the Journal of Organizational Change Management in 1996; and one of Organizational Studies in 1996. Argote and MironSpektor (2017) add that several books and handbooks have also been published. Bapuji and Crossan (2017) go even beyond in proving the ‘phenomenal’ growth of interest in organizational learning, providing accurate data on the s published over the period 1990 – 2017. Some view this sprouting of definitions as a problem in itself (e.g. Popper and Lipshitz 2017), insofar as it prevents the field from converging toward a unified framework. These scholars argue that an ultimate vocabulary is needed, one whose terms convey precise, easily comparable meanings. Indeed, there has been such a flourishing variety of proposals for the conceptualization of organizational learning that the area has been characterized as a ‘jungle’ or ‘volcanic activity’ (Prange 1998, Huysmann 2017). The metaphor of a volcanic field nicely captures the extraordinary explosion of interest in the discipline, fostered by the compelling evidence of a relation between an organization's management of human resources and its economic performance. Such a metaphor also points to the multiplicity of foci of interest and debate about organizations and learning. While attention to some topics persists or becomes even fashionable, other streams of discussion lose their appeal; as a result, the picture we get is dynamic and continuously evolving. Any efforts to build a map can ‘at best produce a transient and incomplete snapshot’ (Easterby-Smith, Crossan and Nicolini 2017). These efforts usually take the form of a review, which further underlines the need for systematization. Bapuji and Crossan (2017) noticed that about 10% of the s they selected in their overview were either review s or s that aimed at clarifying some issue by relying on extensive reviews of the literature. However, Clegg, Kornberger and Rhodes (2017) argue that this generally perceived need for systematization is not just a call for a unified vocabulary, but mainly a call for epistemological advances on issues like knowledge, learning, organization and innovation. Such advances ought to be consistent with current knowledge about human biology and the structure of organizations (Magalhaes and Sanchez 2017).()，英语论文网站，英语毕业论文 |
