Divergent Approaches and Converging Views - Semantic Scholar

Proceedings of the 36th Hawaii International Conference on System Sciences - 2003

Divergent Approaches and Converging Views: Drawing Sensible Linkages between Knowledge Management and Organizational Learning Jing Zhang University at Albany, SUNY [email protected] Abstract Knowledge management (KM) and organizational learning (OL) have developed in both divergent and convergent ways. In particular, these fields have relatively distinct intellectual traditions and conditions that gave rise to disciplines, as well as a certain level of disparity in research focus and view of knowledge. For example, KM focuses more on the content of knowledge and products of managing the knowledge, while OL emphasizes the process of meaning creation, decision making, and growth of learning capability. The two literatures also reveal, however, convergences with regard to the nature of knowledge and knowledge sharing in the organizational context. Thus the two fields have started to establish a consolidated view of knowledge, in which knowledge is related to practice and situated in the historical, social, and cultural context where it is created and acquired. In addition, both fields recognize the multi-level nature of knowledge and learning and are striving to bridge the gap between individual knowledge and collective memories.

1. Introduction Knowledge management and organizational learning are both widely known and practiced in many organizations. In a general sense, knowledge management is often used to describe activities related to identification, codification, measurement, storage, and transfer of all sorts of knowledge, while organizational learning refers to processes that involve creating, sharing, and acting on the understanding and know-how of organizational practices. This paper reviews the history of and current developments in the fields of knowledge management and organizational learning. The primary purpose is to explain divergences and convergences that exist in the two literatures, so as to provide a theoretical foundation for studies involving systematic efforts to manage knowledge and learning capabilities within the organizational context. The connections between these two fields are strong, although they have been relatively independent sources of

Sue R. Faerman University at Albany, SUNY [email protected] guidance for organizational practices [1]. Since both fields deal with organizational knowledge, studies of knowledge management often have an element of organizational learning (e.g., [2], [3]); while studies on organizational learning or learning organizations often include knowledge management as one approach (e.g., [4], [5]). Although overlapping interests can be seen in the historical development as well as in the contemporary writings of these fields, there has been little effort to examine the connections between knowledge management and organizational learning. With an increasing level of interest in both areas, it is important to know where these two disciplines come from, what are the antecedents and conditions for their emergence, what are the differences and similarities in their major focuses, and how they are likely to evolve in the future. While the terms have different meanings, knowledge management and organizational learning have been used interchangeably in many studies and literature reviews. For many practitioners, the terms may carry little difference as to the content and functions of their practices. In theory, however, the lack of clear guidance may impede the development of theories in both directions. More importantly, research on these two streams has many areas of overlap in terms of focus and approaches, especially in the more recent research. This suggests that dialogue between these two fields could produce synergy, and may even facilitate the growth of an integrated view of knowledge-related work. A close examination of the convergent conclusions from divergent perspectives can reveal a better understanding of the nature of organizational knowledge and learning, and why organization knowledge is important, yet difficult to create, share, transfer, and transform. This paper is arranged in five sections. First, the historical development of both fields is introduced. Next, we examine the research focuses of both fields and summarize the major differences. In the next section, we highlight the converging insights derived from synthesizing these two disciplines with respect to the nature of knowledge in the organizational context. Finally,

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conclusions and recommendations for future research are offered.

2. Historical development History may be the most appropriate place to look for the trademarks of knowledge management and organizational learning, providing insights about where they come from, and what they mean today. In this section, we discuss the classic works of these two fields and the conditions that gave rise to these fields.

2.1. Classic works Organizational learning is closely coupled with the development of the fields of organizational theory and behavioral science, and can be traced to two earlier ideas. The first is the of idea of scientific management, the essence of which is to discover the best way to accomplish routine tasks through systematic study and analysis of the work motion; the other is found in March and Simon’s Organizations [6], which noted that an organization’s choice of standard procedures is conditioned by the existing routines, which reflect the organization’s memory or repertories of possible solutions that result from organizational learning processes. Contemporary interest in organizational learning, however, is heavily influenced by Argyris and Schön’s [7] work on organizational learning, which builds on two central concepts. First, the concept of a theory of action distinguishes between espoused theory and theory-in-use. Espoused theory is “the theory of action to which [one] gives allegiance and which, upon request, [one] communicates to others” (p .11), whereas, theory-in-use is “the theory [that] actually governs [one’s] action” (p.11). The second key concept in their work is the distinction between single-loop and double-loop learning. Single-loop learning occurs when the organization takes actions to adjust strategies to reach the expectation, but here learning is limited. Double-loop learning, however, not only connects the error to the strategies, but also to the values and assumptions of theory-in-use. Thus, double-loop learning is necessary for organizational culture changes. Organizational learning, as framed by Argyris and Schön, has also generated critical examination. For example, one classic review by Levitt and March [8] provides a comprehensive analysis of the structural difficulties of organizational learning, focusing on the problems created by fluctuation and complexity of the causal system, ambiguity in interpreting history, and insufficient experience to yield valid conclusions. Several other more recent works have advanced substantially the theories and practice of organizational learning. Senge’s The Fifth Discipline: The Art and Practice of Learning Organization [42] applies systems

thinking to the process of organizational learning. Work by Wenger and colleagues, including Communities of Practice: Learning, Meaning, and Identity [9], Situated Learning [10], and Toward a Unified View of Working, Learning, and Innovation [11] focuses on the notion of communities of practice, which has become a widely accepted concept for studying the process of learning in the organizational context. Alternatively, the study of knowledge management has been centered on Polanyi’s Tacit Dimension [12]. Polanyi used several examples, e.g., the ability to integrate the meaning of the word with the external thing this word denotes and use of tools or probes to illustrate that “we can know more than we can tell” (emphasis in original, p. 4). Polanyi’s analysis emphasized several key concepts. First, the ability to identify the outside objects, and hence to know, is learned through a process of personal experience. Second, tacitness and explicitness are distinct dimensions; the increase of one does not come at the decrease of the other. Third, since tacit knowing is an essential element of any kind of knowledge and is acquired through personal experience (“indwelling”), any effort to achieve absolute “detached, objective knowledge” is misdirected and “selfdefeating” (p. 20). Polanyi is widely cited in the knowledge management literature, but as is true of most works before the 1990s, his work is situated in a philosophical context, and focuses on the definition of knowledge but not on the systematic effort of managing it. The conceptualization of knowledge management did not develop, however, until knowledge became central to production and innovation in the 1990s. Peter Drucker is among the first who advocated the advent of a knowledge society. In Post-Capitalist Society, Drucker [13] documented the transformation from a Capitalist to a Knowledge Society, which began shortly after World War II, noting that the foremost economic resource is no longer capital, land, or labor. Rather, “(i)t is and will be knowledge” (emphasis in the original, p.8). The field of knowledge management has also been shaped by the experience and philosophy of Eastern society. Nonaka and Takeuchi’s Knowledge-Creating Company, based on experience in Japanese companies, is a pioneer work in mapping explicit and implicit knowledge, as well as individual, group, and organizational knowledge into one matrix demonstrating the dynamics of knowledge creation [14]. According to Nonaka and Takeuchi, organizations are not only capable of processing information acquired from outside, but also create new knowledge from inside by redefining the problems and solutions, as well as the environment. Nonaka and Takeuchi argue, “Organizational knowledge creation is a continuous and dynamic interaction between tacit and explicit knowledge” (p. 156). Knowledge conversion involves socialization (tacit knowledge to tacit knowledge), externalization, (tacit knowledge to explicit

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knowledge), combination (explicit knowledge to explicit knowledge), and internalization (explicit knowledge to tacit knowledge). Since knowledge management is still an emerging discipline, representative works are still unfolding. Among the proliferating literature in the field since the 1990s, a few key pieces shed light on the theories and practice. Kogut and Zander [15, 16] and Grant [17] link knowledge management to the theory of the firm and developed the notion of knowledge-based theory of the firm. Teece [18] ties knowledge management to strategic management, and translated the theories of core competence and industrial/organization theories to a knowledge-based view of strategy in achieving competitive advantage. Cook and Brown [19] treat explicit, tacit, individual and group knowledge as four “distinct and coequal” forms of knowledge, generating fresh interest in studying epistemologies in the management context. While there are clear similarities across the concepts of these fields, they build on separate and distinct literatures. In the following section, we examine the antecedents at the time those works were developing that influenced how researchers and practitioners handled the problems they were struggling with.

2.2. Conditions giving rise to disciplines According to Argyris and Schön, effective learning emerged as a concept in the 1970s as a reaction to failures of professional action in areas such as urban renewal, housing, criminal justice, social services, and education during the 1960s [20]. They argued that the solutions to these problems that were being proposed were based on a simplified and static view of the economic, political, and technological environment; and thus created problems that were more complicated than the problems that they were intended to solve originally [7]. According to Schön [20], the conditions that confront practitioners can be characterized as complex, unstable, uncertain, unique, and having value conflicts. Complexity intervenes when practitioners encounter problems that cannot be handled by their traditional education. Even when professional knowledge can be updated to meet new demands, the improvement will soon be defeated by the unstable environment, such as those introduced by the rapid changes of technologies. The environment of practice is further characterized by uncertainty and indeterminacy, where traditional techniques, mathematical models and algorithms are misleading in solving interconnected problems in turbulent environment. In addition, the majority of the tasks that professionals handle are unique, with each problematic situation requiring adaptive solutions that are not prescribed in standard textbooks. Adding to the difficulties are the conflicting values and goals that practitioners encounter. Argyris and

Schön [7] argue that most organizations exist in a “predictably unstable” environment, and so “[t]he requirement for organizational learning is not an occasional, sporadic phenomenon, but is continuous and endemic to our society” (p.9). Facing such environments, some practitioners are able to restructure situations that are complex and uncertain; yet they are often unable to account for the artistry they display in daily practices. The development of knowledge management, on the other hand, has been driven by practices and development in information and data management. It developed first in areas that are knowledge intensive, such as consulting, research and development, and pharmaceuticals, and was then adopted by other areas [21]. Development of the field has been fostered by changes in economic development, technologies and social and organizational structures. 2.2.1. Economic environment changes. In his introduction to a series of knowledge management books, Prusak [48] argued that the rise of interest in knowledge is related to globalization and the awareness of the value of knowledge at a societal level as well as at a level of individual production units. Advances in transportation, computing and telecommunication technologies, as well as the decline of centralized economies have propelled the creation of a global market. While the profit potential of distributing products and services to wider markets and fully utilizing an unbounded labor market is attractive to managers, it also requires them to handle unprecedented complexity, as well as to know what they know, who knows it, and what they do not know that they should know [1]. Furthermore, they need to tackle the problem of sharing knowledge and understanding work across distributed offices [22]. Knowledge management has thus grown out of an understanding of the critical value of knowledge for economic growth and prosperity. Since Drucker [13] first foresaw the arrival of a knowledge-based economy, it has been widely recognized that knowledge is a critical factor of production that needs to be accounted for and nurtured [23]. Neef [25] noted that the growth of a service-based economy is highly dependent upon knowledge and skills that allow for “complex problem solving, technology innovation, creative exploitation of new markets, and the development of new product or service offerings” (p. 2). At a microeconomic level, firms recognize that knowledge, often in the forms of intellectual assets and know-how, is necessary for long-term competitive advantage [24]. The competitive power of knowledge-based firms is often derived from the ability to exploit markets and to innovate [25]. Different from the mechanism of diminishing returns governing the equilibrium of markets for goods-based production, the market of knowledge-based productions tends to be characterized by increasing returns [26]. Advantage and disadvantage are reinforced; whoever wins

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(or loses) first is likely to win (or lose) further [18], leading to efforts to identify sources and carriers of knowledge, measure the strategic value of tangible and intangible assets, and invest in knowledge. The aim is to compete on a capability that can be easily transferred within the firm but hard for others to imitate [27]. 2.2.2. Technology changes. The development of information technology, especially telecommunication and networking, facilitates the exchange and storage of information and knowledge. With the ubiquitous deployment of increasingly powerful computing and networking infrastructures, it is possible to exploit knowledge by aggregating large amounts of data from various sources. The development of knowledge management is thus related to developments in the 1970s and 1980s in areas such as records management, management information systems, decision support systems, and artificial intelligence. Many technologies used in knowledge management are natural extensions of technological solutions in those areas, such as data warehouses, data mining techniques, software agents, Web, intranets, and Internet. Researchers and practitioners are not limited to efforts to organize the codified messages; they have also started to explore tools that support knowledge creation and exchange across different forms of knowledge [28]. While the development of technology automated much production and processing, it did not replace the need for human knowledge. Instead, it has generated greater demand on human skills and knowhow to evaluate the value of knowledge, make decisions using available information, and design effective systems. 2.2.3. Social and organizational changes. Economic and technology developments have also been accompanied by changes in the social and organizational landscape. Drucker [13] argued that in the post-Capitalist society, the distinction between bourgeois and proletarian social classes disappear, and are replaced by two groups of workers—knowledge workers and service workers. With the growth of the population of knowledge workers and their production capability, it is increasingly important to identify, nurture, account for and share knowledge that substantially comprises their inputs and outputs. Recent developments in the practice of management, such as reengineering and total quality management, have also created and institutionalized organizational structures, as well as values and mindsets favoring empowerment, decentralized decision making, systematic measurement, and cross-functional teaming [29]. These all provide a fertile field for knowledge management to grow. In summary, knowledge management and organization learning have relatively distinct origins, and the intellectual traditions of both disciplines are influenced by diverse disciplines. For knowledge management, the focal

disciplines include Information System, Library Science, Artificial Intelligence, Management, Sociology, Education, and Economics, and early works focus on theories of the knowledge-based firm, core competences, epistemology, knowledge assets, and intellectual capital. For organizational learning, the key disciplines are Organizational Behavior, Organizational Theory, Human Resources Management, Psychology, and Management, and studies within those disciplines developed concepts and theories of double-loop learning, espoused theory, theory-in-use, systems thinking, and communities of practice (see Table 1). Table 1. Summary comparison of knowledge management and organizational learning Knowledge Management Focus Disciplines

Content and products Information System, Library Science, Expert Systems and AI. Management. Sociology, Education, Economics

Classic Works

The Tacit Dimension [12] Post-Capitalist Society [13] The Knowledge Creating Company [14]

Representative Works

Knowledge of the Firm, Combinative Capabilities, and the Replication of Technology. [15] What Firms Do? Coordination, Identity, and Learning [16] Toward a Knowledgebased Theory of the Firm [17] Bridging Epistemologies: the Generative Dance Between Organizational Knowledge and Organizational Knowing [19] Strategies for Managing Knowledge Assets: the Role of Firm Structure and Industrial Context [18] Knowledge-based firm Core competence Epistemology Knowledge assets Intellectual capital Transformation from viewing humans as the discoverer or processor of knowledge to humans as the creator of knowledge Explicit vs. tacit knowledge Knowledge vs. knowing

Themes/ Constructs/ Theories View of Knowledge

Dimensions /Types of Knowledge

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Organizational Learning Processes Organizational Behavior, Human Resources Management, Organizational Theory, Psychology, Management Organizations [6] Organizational Learning: A Theory of Action Perspective [7] Organizational Learning [8] The Fifth Discipline: The Art and Practice of Learning Organization [42] Situated Learning [10] Organizational Learning and Communities of Practice: Toward a Unified View of Working, Learning, and Innovation [11] Communities of Practice: Learning, Meaning, and Identity [9]

Double-loop learning Espoused theory Theory-in-use Systems thinking Communities of practice Socially constructed and highly dependent upon “mindset” Theory-in-use Practice-embeddedness Community-

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Aim

Know-what vs. know-how Individual vs. collective Competitive advantage What organizations know

embeddedness Dynamic Innovation Changes How organizations know

3. Diverging focuses and perspectives Studies of knowledge management and organizational learning not only differ in terms of intellectual traditions, they also display certain disparities in research focus and the view of knowledge (see Table 1). It should be noted, however, that while the distinction we make between these disciplines allows for theoretical clarification, in reality, the boundary is far less distinct than as presented in Table 1. Distinctions are thus presented in terms of degree. For example, we argue that most studies of knowledge management have a stronger focus on the content and products of knowledge management, while most studies of organizational learning place greater emphasis on the processes of inquiring and learning, acknowledging that knowledge management also pays attention to the process of knowledge creation and transmission and organizational learning is also concerned with the end results of learning.

3.1. Focus 3.1.1. Knowledge management focus: content and structure of knowledge. To a great degree, knowledge management emphasizes the content or the end-results, of identification and evaluation. Knowledge is seen, however, as the starting point as well as the purpose of knowledge management. Knowledge is thus a commodity to be identified, captured, codified, retrieved, stored, and evaluated. The systematic effort is often to strive toward the transformation of intangible assets into tangible forms—a searchable repository, or patents, trademarks, reputation, and network. Most studies of knowledge management, therefore, start by specifying the content and structure of knowledge. This emphasis has generated extensive discussion of the hierarchical aspects of data, information and knowledge. A commonly held view saw “[d]ata as simple facts that become information as data is combined into meaningful structures, which subsequently becomes knowledge as meaningful information is put into context and when it can be used to make predictions” [30 p.1]. This hierarchical perspective has lost its popularity because the hierarchical assumption cannot be defended; moreover, it rarely offers any practical guidance to practitioners [31]. Indeed, Tuomi [30] argues for an inverse order; knowledge must exist before the formulation of any information and information must precede the creation of any data. Discussion of the content and structure of knowledge is not limited to what it consists of; it is increasingly focused

on differentiating various types or dimensions of knowledge. The generally accepted classification is along the line of explicitness and tacitness [14]. While explicit knowledge is the set of rules, procedures, and relationships expressed by languages and other artifacts, tacit knowledge refers to the subjective understanding and intuition that is not directly expressed, and encompasses the not-easily expressed as well as the not-expressible. Knowledge is also seen as carried by the individual or the collective [14, 19], residing in procedural or declarative memory [16], and sticky when transferred within the organizations and leaky when it flows to competitors [32]. As a whole, the motivations for classifying knowledge into various types are three-fold: (1) to facilitate the theoretical development in this field; (2) to align the strategies and the design of technology with the need to support the sharing of different types of knowledge, and the transformation of knowledge across different types [33]; and (3) to identify the value of each type so as to focus the organizational resources on the development of the most valuable one. Scholars do not necessarily agree on which type of knowledge is most important. Studies in the early stages tended to give greater credit to explicit knowledge than to tacit knowledge, based on the rationale that the explicit knowledge can be easily and widely distributed, and therefore effectively leveraged. Increasingly, it has been recognized that tacit knowledge is the essential element for competitive advantage as it is embedded in practice within a firm, and therefore, easy to communicate and coordinate within the boundary, yet difficult to be replicated outside of the boundary [15]. In addition, explicating knowledge may create inflexibility that impedes performance and changes [33]. The current understanding is that they are equally valuable, as the comprehension of either one cannot be accomplished without the existence of the other [19]. 3.1.2 Knowledge management focus: quantification and measurements. The strong focus on content and product is also reflected by the deliberate attempt to quantify, measure and evaluate knowledge assets in the knowledge management literatures. A balanced scorecard is developed to make the knowledge development accountable to the organizational long-term objectives [34], measuring employee capabilities, information system capabilities, and motivation, empowerment and alignment in various ways. Similar efforts to measure knowledge in tangible and intangible forms are also elaborated in the work of Bohn [35] and Sveiby [36]. 3.1.3. Knowledge management focus: economic and technological outcomes. The end products of knowledge management are often the concrete economic or technological outcomes that can be accounted for. Thus, even though technologies are largely viewed as a means to

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the ends, they became inseparable parts of the results, and sometimes become the ends themselves. For instance, Earl [37] generated a taxonomy that classifies knowledge management into systems, cartographic, engineering, commercial, organizational, spatial, and strategic schools of thought. The first four schools are especially obvious in their intention of bringing about concrete products. For instance, the systems school, the longest established approach, intends to capture experience and expertise of the specialists in codified form and organize those in knowledge-based systems so that the knowledge is widely accessible to other specialists. The result is the enlarged knowledge bases. Other technologies such as “yellow pages” types of systems, shared databases across tasks and geographies, and intellectual register and process systems are also extensively used in other schools. The maximized economic return of knowledge as well as an increasing number of intellectual properties are the final outcomes. 3.1.4. Organizational learning focus: process of meaning creation. Unlike the product-centric approach of knowledge management, organizational learning focuses on processes of knowledge acquisition. Studies examine the dynamic processes of meaning creation and decision making, as well as the growth of learning capabilities. Organizational learning highlights the social and negotiated process of meaning creation [9, 11]. Wenger [9] argues that meaning is not pre-existing, but is created through the process of negotiation of meaning. He argues, “[b]y living in the world we do not just make meaning up independently of the world, but neither does the world simply impose meaning on us. The negotiation of meaning is productive process, but negotiating meaning is not constructing it from scratch. Meaning is not pre-existing, but neither is it simply made up. Negotiated meaning is at once both historical and dynamic, contextual and unique.” (p. 54) The negotiation process is not just concerned with reaching an agreement between people; it also involves a sense of continuous interaction and (re)adjustment to attain understanding, although it does not necessarily involve direct interaction with other people. Negotiating meaning involves two interactive processes—participation and reification. Participation refers to the social processes of active involvement while being a member of social communities. It includes processes such as acting, thinking, feeling and belonging. Reification refers to the process of “giving form to our experience by producing objects that congeal this experience into ‘thingness’” (p. 58). It includes a wide range of processes, such as designing, representing, encoding, and interpreting. Wenger [7] maintains that participation and reification are two complementary processes, which cannot replace each other. Participation make up the disconnectedness and misalignments in reification and reification repairs the

ambiguity and locality of participation. The increase of one does not come at the decrease of the other; on the contrary, high levels of participation tend to require intense reification to bring intuition into form, and high levels of reification demand intense intuitive participation in order to make sense of the expressions. 3.1.5. Organizational learning focus: process of decision making. Studies in organizational learning are also interested in untangling the mystery of intuitive processes of decision making by practitioners [38]. Crossan et al. [38] point out that learning is more than a conscious and analytical process; it involves preconscious recognizing and comprehending of patterns and possibilities. Studies on intuition suggest that intuiting is learned through a process of past pattern recognitions and it accumulates after a long period of immersion in the problem. Based on intuition, an expert can discern patterns or generate insights that novices cannot [39]. However, after practitioners acquire a sophisticated understanding, they are no longer able to think consciously and/or articulate the once conscious and deliberate thoughts [20]. Acting becomes spontaneous, simultaneously intertwined with thinking. Studies of organizational learning, however, are not satisfied with individuals’ capability to make subconscious decisions; they are more interested in the interactive process of intuition and institutionalization, the development of metaphors, stories, and organizational routines to facilitate the communication and dissemination of understandings about work. It should be noted that although routines represents products of organizational learning, the content and structure are not as much a focal interest as are the dynamic processes of interpreting, reinterpreting, and transforming of routines [7, 8, 40]. Although some theorists insist that learning must be beneficial in order to be called organizational learning [40], others have recognized that the inherent difficulties of the learning process lead to non-beneficial or less-thanoptimal decision making [8, 38]. Levitt and March [8] raise the question of “competency traps” (p.322). When an organization chooses among alternative routines, its choice often reflects its current competence with it. The chosen one may be far from optimal; however, it can lead to favorable performance as a result of learning. To change, however, the organization has to collectively abandon the proven success and allow unproven risk taking. 3.1.6. Organizational learning focus: growth of learning capability. Different from knowledge management’s general pursuit of quantifiable results, organizational learning places substantial emphasis on learning capability as the purpose of learning. Learning thus becomes an end, not simply a means [41]. For some scholars in organizational learning, the results of learning is not a discrete body of knowledge that can be portable

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and reapplied in other contexts, but the skills to participate and further engage in the process of participation [10]. Much of the research addresses the need to move away from superstitious or first-order learning to substantial or second-order learning [7, 8, 40]. Change can be brought about by first-order learning, but actions resulting from such direct causal deduction can go wrong for various reasons [8]. Learning, therefore, should not only target changes, but also the capability for change or the ability to pursue second-order learning, which takes a non-routine position, paying attention to the assumptions and rationale behind the knowledge. Therefore, it can become a means for transforming the culture and values systems that foster the ability to learn further [41]. To summarize the literature on organizational learning, the learning process, as well as the resulting knowledge, has several characteristics. First, understandings are embedded in actions, and not only reflected in cognition. Sharing may require a level of common experience or coparticipation to facilitate the development of shared understanding. Second, understandings are situated in the context where the meanings are created. The richness and depth of the knowledge cannot be acquired without consideration of the history, culture, and social dynamics of the communities of practice. Third, the process of organizational learning is inherently dynamic and therefore cannot be readily reduced to analytical and system structures.

3.2. Views of knowledge The differences in research focus between knowledge management and organizational learning have been shaped by different views of knowledge. Despite the early definition by Polanyi and a recent growing understanding of knowledge from a social-practice perspective, a substantial segment of the studies of knowledge management still attempt to distinguish subjective and objective knowledge, with the assumption that knowledge exists independent of the agents and social context, and that there are objects that can be identified, measured, standardized and moved around. Cook and Brown [19] raised criticisms that much work on knowledge management is based on a traditional understanding, which can be called an “epistemology of possession,” since it views knowledge as something people possess (p. 381). For many knowledge management scientists, the development of technology provides an opportunity to convert soft knowledge into hard knowledge. Scholars of organizational learning, however, tend to subscribe to the socially constructed view of knowledge. “Meaning exists neither in us, nor in the world, but in the dynamic relation of living in the world” ([9] p. 54). The misleading notion of Technical Rationality, ignoring the problem setting and processes of decision making, was the

very limitation that early organizational learning scholars were trying to break through. Schön [20] argued, “[i]n real world practice, problems do not present themselves to the practitioner as givens. They must be constructed from the materials of problematic situations which are puzzling, troubling, and uncertain” (p. 40).

4. Converging view on the nature of knowledge and knowledge sharing in organizational context In this section, we focus on the converging perspectives of knowledge management and organizational learning along three key themes: epistemology, dimensions of knowledge, and knowledge transfer and transformation across different levels. Interestingly, some of the converging points are also the diverging areas discussed in the previous section. They initially appear to be diverging because each was built upon relatively distinct premises in the early stage, and, in some cases, the new developments have not achieved a dominant presence or central focus. However, there are growing understandings in both disciplines regarding knowledge and organization that enable some level of convergence on the nature of knowledge in the organizational context.

4.1. Epistemology There is a converging trend with regard to what knowledge is and how we know. In his chapter, From Capitalism to Knowledge Society, Drucker [43] captures the radical changes in the meaning of knowledge from a historical perspective. He states that there is a growing movement from “knowledge to knowledges” (p. 29), and a shift from viewing knowledge as “being” to examining knowledge in terms of its utility in “doing” (p. 15). Similarly, as Gherardi and Nicolini [44] noted, a growing body of literature has established that organizational knowledge can be viewed as distributed social expertise, “knowledge-in-practice situated in the historical, sociomaterial, and cultural context in which it occurs” (p. 330). This is consistent with the organizational learning perspective, which views knowledge as understandings associated with practices and inherently social and constructive. Knowing, in this context, entails individuals’ cognition as well as actions. Organizational knowledge is acquired by a process of participation in communities of practice, or “indwelling.” We can not know unless we act on the situations to which we give meaning. This process of knowing is also characterized by interactions between participation and reification [9], conversion between tacit and explicit knowledge [45], or a dance between knowledge and knowing [19].

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4.2. Dimensions of organizational knowledge

4.3. Individual, group, organizational knowledge

Studies of types of knowledge from knowledge management and knowledge creation processes from organizational learning are also forming a common understanding about the properties of organizational knowledge. Here, we choose to describe those properties with a set of dimensions, rather than types, building on recent works that consider the interplay of artifacts, shared context and practice, and the dynamic processes of knowledge creation [9, 45, 46]. These dimensions are: • Codifiability - the ease by which knowledge is expressed in artifacts and symbols • Practice-embeddedness - the degree to which knowledge is acquired in the ongoing practice and through learning by doing • Context-embeddedness - the degree to which knowledge is situated in the historical, social, and cultural context in a community of practice • Dynamic - the degree to which knowledge is constantly recreated and transformed. These four dimensions are fundamental, although not independent, elements of knowledge, and can be used to analyze other characteristics of knowledge, such as “transferability,” “capability for aggregation,” and “product observability” [27]. Knowledge can be viewed as having all of the above four properties, but to different degrees. The overall transferability of knowledge, for instance, is directly related to the mixture of its position on each of the above four dimensions. Sharing knowledge that is resistant to codification, deeply embedded in practices, involves diverse communities of practice, and intensely dynamic is inherently more difficult, and therefore requires higher levels of organizational structural and procedural support to coordinate the sharing activities. Two clarifications need to be made with regard to this set of dimensions. First, codifiability is different from the tacit and explicit distinction. Not all tacit knowledge can be expressed in artifacts and symbols; and there are also cases where explicit knowledge cannot be codified or has not been codified simply because no theory or schema by which to identify and represent knowledge exists [15]. Second, it may be difficult to distinguish between the dimensions of practice-embeddedness and contextembeddedness. These two are interrelated, but do not function in exactly the same way. The practiceembeddedness and context-embeddedness distinction may be similar to the two dimensions of tacit knowledge described by Takeuchi [47]. The first is the “technical” dimension, which includes hard to express or nonexpressible personal skills or crafts derived from bodily experience. The other is the “cognitive” dimension, which encompasses beliefs, perceptions, and mental models that are acquired from one’s social-cultural background.

Another common interest between knowledge management and organizational learning is that both consider knowledge and learning as multilevel and strike to bridge the gaps between the knowledge of individuals and those of collectives. Many scholars [15, 38, 40, 45] hold the position that learning occurs to individuals but is also expressed in group, organization, or network routines. The acquisition of knowledge at the organizational level is ultimately influenced by individuals’ thinking and acting. However, knowledge is carried by and located in the organizational context where knowledge is created and (re)interpreted. The notion of organizational knowledge may be devoid of meaning if it only means the aggregation of individual knowledge.

5. Conclusion This literature review has examined divergences and convergences of the fields of knowledge management and organizational learning. The review found that the paths of their development are relatively distinct due to different intellectual traditions and conditions giving rise to disciplines. More importantly, the two fields have some differences in research focus and view of knowledge. The literature review also reveals that there are growing convergences with regard to the nature of knowledge and knowledge sharing in the organizational context. Despite early epistemological differences, the fields of knowledge management and organizational learning have started to establish a converging view of knowledge, seeing it as related to practice and situated in historical, social, and cultural context where it is created and acquired. In addition, the two fields have a common interest. They both recognize knowledge and learning as multilevel; and both fields attempt to understand the nature of knowledge and learning processes at different levels and try to bridge the gaps between the knowledge of individuals and those of collectives. This conclusion has several implications for the future studies. First, the study of knowledge-related work should consider the theoretical implications of focusing on one or the other, or the combination of both. The premises, theories, terminologies, and focus may not be overlapping. Researchers should adopt the appropriate theoretical framework for the specific set of research questions. Second, the converging trend suggests a rewarding direction for future research. Each discipline alone can not offer a focus and understanding as comprehensive as the integrated framework. Organizational learning has been criticized for giving too little account to the barriers that hinder learning and for failing to specify the concrete business and economic outcomes of learning [1].

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Conversely, the field of knowledge management does not capture the dynamic action taking and knowledge creation found in learning theories [38]. Research that considers of the strength of both, the production and structure orientation of knowledge management and the process orientation of organizational learning, can lead to more practical and relevant results about knowledge-related work. This literature synthesis also points to limitations in the current knowledge management and organizational learning literatures. First, most of the studies are conducted in the private sector, with scant attention to knowledge sharing and learning in the public sector or public-private partnerships. Given its need to adapt to the changing environment and react to the uncertainty and fluctuation, as well as the knowledge-intensive nature of the work conducted in the public sector, there are enormous needs to study the dynamics of knowledge transfer, the impact of learning and knowledge sharing, and the conditions that facilitate and impede the development of knowledge and effective learning. Second, the frameworks of learning and knowledge transfer are mostly limited to within organizational boundaries, and so interorganizational knowledge transfer is primarily discussed under the context of competition, rather than collaboration. In today’s world, it is important to understand how the nature of knowledge and the processes of knowledge creation influence collaborative efforts to share knowledge across the boundaries of organizations.

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