Mainstream economics 6 depicts actors as rational agents facing known and calculable risks and driven by the aspiration to make optimal decisions. In contrast, evolutionary economics of innovation posits that uncertainty is an inherent feature of innovation processes and optimisation, therefore, is excluded on theoretical grounds. Further, while the availability of information has been a focal question in mainstream economics for decades, a major lesson of the evolutionary account of innovation is that firms’ per- formance is determined by their accumulated knowledge — both codified and tacit — and skills, as well as learning capabilities. Information can be obtained via normal market transactions, and thus mainstream economics can readily treat information as a special good. 7 In contrast, knowledge cannot be bought and used instantaneously—and that applies a fortiori to the types of knowledge required for innovation (how to exploit readily available pieces of information in a new way, e.g. by combining information on different subject matters, how to utilise experience and skills accumulated through pre- vious search processes, and how to assemble these various types of knowledge). One must go through a learning process to acquire knowledge and skills, and it is not only time-consuming, but the costs of trial and error need to be incurred as well. Hence, the uncertain, cumulative and path-dependent nature of innovation is reinforced. Cumula- tiveness, path-dependence and learning lead to heterogeneity both at micro and meso levels (Castellaci 2008; Dosi 1988; Dosi et al. (eds) 1988; Fagerberg et al. (eds) 2005; Hall and Rosenberg (eds) 2010; Malerba 2002; Pavitt 1984; Peneder 2010).
Various schools of economics focus on different research questions, devise and follow specific axioms and assumptions, and rely on a certain set of preferred methods, e.g. econometrics, game theoretical models, simulations, controlled experiments or qualitative analyses. Innovation – technological, organisational, managerial changes and opening up new markets – had been a major theme in classical economics. Then neoclassical (general equilibrium) economics essentially abandoned research questions concerned with dynamics, and instead focused on static comparative analyses and optimisation. Technological changes were treated as exogenous to the economic system. More recently, given compelling empirical findings and new theoretical insights on firm behaviour and the operation of markets, various branches of mainstream economics 1 have relaxed some of the most unrealistic assumptions of neoclassical economics, and put innovation back on the research agenda. For evolutionary economics of innovations, in contrast, since its foundation innovation has been the central theme, and this paradigm has also developed a diametrically different theoretical framework to analyse its core questions. These competing schools, however, now share some major claims: innovation contributes to enhanced productivity to a decisive extent, creates new opportunities to increase profits, and thus improves competitiveness at the micro level. Further, it has significant impacts on several macroeconomic indicators, too, including growth, the structure of the economy and foreign trade, balance of payment, investments, and employment. 2 These schools, although consider different types of knowledge as major inputs for innovations, also share the view that universities and publicly financed research organisations (PROs) are major actors.
ABSTRACT: Knowledge, during the last few decades, has become the central capital, the cost centre and the crucial resource of the economy. The construction industry is a knowledge based industry and the production of knowledge is vital for projects and organizations, in order to tackle the fast changes and to be innovative. Knowledge production is influenced by variety of organizations, projects as well as by the nature of the industry in construction domain. This research has focused on establishing how the characteristics of the industry, individual projects and the organizational culture influence knowledge production by promoting or inhibiting the knowledge production within the Sri Lankan context. This study identifies and analyses different types of knowledge sources, main triggers of knowledge production and the promoters & inhibitors of knowledge production from project, organizational culture and industry perspectives. It was found that contracting organisations mostly rely on internal knowledge sources for their knowledge acquirement. The results indicates that the knowledge production takes place through ‘learning how’ and ‘learning why’ and identifies ‘learning how’ as the dominant process within the Sri Lankan construction industry. In addition it reports that knowledge production seems to focus on project delivery rather than strategic issues.
If we continue to build knowledge collections fo- cused on specific types, will we collect a sufficient store of common sense knowledge for understand- ing language? What kinds of knowledge might lie outside the collections that the community has fo- cused on building? We have undertaken an empir- ical study of a natural language understanding task in order to help answer these questions. We focus on the Recognizing Textual Entailment (RTE) task (Dagan et al., 2006), which is the task of recogniz- ing whether the meaning of one text, called the Hy- pothesis (H), can be inferred from another, called the Text (T). With the help of five annotators, we have investigated the RTE-5 corpus to determine the types of knowledge involved in human judgments of RTE. We found 20 distinct categories of common- sense knowledge that featured prominently in RTE, besides linguistic knowledge, hyponymy, and syn- onymy. Inter-annotator agreement statistics indicate that these categories are well-defined. Many of the categories fall outside of the realm of all but the most general knowledge bases, like Cyc, and differ from the standard relational knowledge that most auto- mated knowledge extraction techniques try to find.
Scharmer (2000 )argues that there are three types of knowledge, explicit, tacit and self- transcending knowledge. Gore and Gore (1999) divided knowledge into three types, truly tacit knowledge, technical tacit knowledge and cognitive tacit knowledge. For Spender (1994) knowledge can be classify into four types, individual tacit knowledge, individual explicit knowledge, explicit collective knowledge and collective tacit knowledge. Architectural and component knowledge are two types of knowledge, according to Henderson and Clark (1990). Stewart (1997) views knowledge to be cognitive knowledge, advance skills and self- motivated creativity. Nickols in Gourlay (2001 ) divided knowledge into implicit knowledge, declarative knowledge and procedural knowledge. Goal-setting/Idealistic knowledge, pragmatic knowledge, systematic knowledge and automatic knowledge are the categories of knowledge by Wiig (1993). Edvinsson and Malone(1997) have product knowledge, process knowledge and routine knowledge. Lundvall and Johnson(2002) have four categories of knowledge, know-what, know-how, know-why and know-who. Baumard (1999) have implicit and tacit knowledge.
As indicated in section 3, the types of knowledge are tacit, coded and theoretical. Although in practice all types of knowledge exist for every individual, this does not mean that uniform distributions exist. It is to be expected that with regard to various tasks one type is dominant. The determination of the dominance of a knowledge type can be accomplished for one individual, for all individuals and for the separate tasks out of which the organizational process exists. Theoretically, eight possible combinations of dominance ( ) and subordination ( ) can be determined. However, the absence of any or the presence of all dominant type(s) are equivalent. Seven combinations remain: from tacit: , coded: and theoretical: , to tacit: , coded: and theoretical: knowledge. Now we will turn away from the knowledgetypes and organizational processes and direct our attention to the other end of the spectrum where the organizational forms are labeled. Many labels can be found (Sorge, 2001), but the most prominent ones are from Thompson, Mintzberg and Boisot. With regard to forms of organizations, Thompson (1967) describes coordination within an organization in terms of (task or process) interdependence, such as pooled interdependence, sequential interdependence and reciprocal interdependence. Pooled interdependence concerns independent departments, that is to say a divisional structure. Sequential interdependence relates to the situation where the output of A is the input for B. In reciprocal interdependence the output of A is the input for B and the output for B is the input for A. In describing the development of organizational forms, Mintzberg (1983) enumerates five forms: a simple structure, a machine bureaucracy, a professional bureaucracy, a divisionalized form and an adhocracy. Boisot (1995), who in a similar way as Mintzberg deals with the evolution of organizations, makes a distinction in fief, clan, market and bureaucracy. Boisot distinguishes organizations in terms of the codification, the concreteness and the diffusion of information. The organizational forms discussed by Thompson, Mintzberg and Boisot are based on decomposition structures, ways of coordination and the characterization of information. Other divisions take into account the authority relation - for example, the subdivision into monarchy, bureaucracy, aristocracy, meritocracy, democracy or technocracy (see also Sorge& Warner, 2001) -, institutional factors (Williamson, 1975) or organizational strategies (prospector, defender, analyzer, reactor; Miles & Snow, 1978).
intact. The verbs in the statements describe the intended cognitive process and the nouns describe the knowledge students are expected to acquire or construct. After specifying the intended cognitive processes and types of knowledge involved in the standards of both fields, they were coded and transferred to separate checklists. Intra-rater reliability was measured by reanalyzing the standards three weeks after the initial analysis to ensure that they were placed in the correct cells in the taxonomy. The Kappa coefficient statistic proposed by Cohen (1960) was used to calculate intra-rater agreement. The values of Kappa Measure of Agreement for the TEFL and ET standards were 0.80 and 0.85 respectively with a significance level of p<.0005. In order to specify if there was a special pattern in the occurrence of different levels of thinking skills in general and critical thinking skills in particular in both fields, the checklists were compared and the frequency and percentage of the cognitive processes and types of knowledge involved in curriculum standards related to each of the fields were calculated.
accordingly, it seems an inadequate formulation to deal thoroughly with all the possible levels and types of knowledge that analysts can and might deploy in the course of their research. Moreover, it does not seem to address complex social worlds, where there may be a highly developed division of labour, and where competence is distributed differentially. It is, we shall argue, hard to see how the most ambitious of researchers could hope to acquire any serious level of ‘competence’ across a variety of specialised fields of activity. And, further, we really do need to reflect further on what might count as ‘competence’. It really is not a straightforward matter. There are different types of specialist knowledge, even within the same general social or cultural field, and the ethnographer of esoteric knowledge, expertise, competence, or whatever one might call it, really needs to have a sensitive grasp of what they might be.
Practical implications. Creating awareness on the subject of knowledge retention and the impact of knowledge attrition, could be a first step towards achieving knowledge retention. To identify essential types of knowledge, awareness of the types of knowledge and skills employees use for completing tasks should be confirmed. If this is not the case, certain knowledge areas could be overlooked. Within this study, obstacles were revealed and a list of criteria, that could be applied to existing knowledge retention strategies, was composed. The insights that were retrieved, as well as the composed list of criteria, may be useful for organisations that wish to implement a knowledge retention strategy. For example, becoming aware of the obstacles, that can apply to TMSs and knowledge retention, could aid an
The ethnographic methods brought to bear here not only trace the contours of the relationships between patrol workers and government officials but also provide an opportunity for me to reflect on my own regrettable implicitness within these broader dynamics and processes of knowledge production. As will become apparent, it is not simply a case of some types of knowledge (‘local’ or ‘expert’) being more equal than others. I am also interested in examining the relationship between lay and desktop knowledge; and in exploring why some types of information might be seen as less credible, less trustworthy. Further, the different ways in which different types of knowledge are dismissed or taken up in Aboriginal policy‐making and the reasons why is a focus of my research. Thus my overall intent in this article is to elucidate these power relations and to reflect on ways to challenge seagull syndrome in everyday contexts, both within academia and policy‐making.
reason for this was that the traditional paradigm for problem solving with expert systems was based upon an explicit model of the domain implemented using rules - mostly, shallow heuristic rules. The attempts to incorporate explanation facilities were first attempted with the heuristic rule-based expert system MYCIN during the late 1970’s . During this time, the potential for explanations became apparent because of the way that the explanation chain links problem with solution. This gave developers access to structures for explanation facilities which provided a free adjunct within the development tools available. Nevertheless, researchers soon discovered that, without further effort, they would not provide adequate quality to attract enough attention from users (; ). The explanatory inadequacies of MYCIN were also evident in many other systems under development at that time, in that they had attracted little or no interest from end-users (; ). For example,  point out that: “Some expert systems had been developed without any explanation component at all”. They elaborate further by saying that in two cases – a route planning system and a manufacturing selection system – the client had stipulated that explanations were unnecessary and confusing. This reflected the general feeling towards explanation facilities at that time. They were perceived as being better suited to knowledge engineers - for validating system knowledge and testing - than for end-users of the system. For, in those early systems, the available explanations were little more than a trace of the detailed problem-solving steps - sometimes enhanced by canned text. Many other shortcomings of expert system explanation were identified by  when he tried to use the MYCIN medical diagnosis expert system for training of junior consultants. His research led to his formulation of an epistemological model that used three types of knowledge: these comprising trace, justification and strategic knowledge. Later, a fourth category called terminological knowledge was added which is a sub-category of justification knowledge.
Most informants brought examples of how prior knowledge (or lack of it) influenced their decision making during the critical incidents they experienced. They therefore found it imperative that explicit knowledge was created from crises that the organization has experienced itself, knowledge gained from crises that other organizations went through (Nathan & Kovoor-Misra, 2002) and knowledge acquired from expert third parties should be properly documented and stored in the organization’s knowledge repositories. The flow of institutionalized crisis knowledge begins from these repositories and is all about the sharing and integration of this knowledge. Most informants associated this flow of knowledge with terms such as “scripts”, “frames”, “standard operating procedures”, “posters”, “courses”, “ten- minute-trainers”, “pocket memos”, i.e., what Schulz and Jobe (1998) call codified knowledge being disseminated throughout the organization. However, this codification is appropriate only for certain types of knowledge that can be explicitly described (Johnson & Lundvall, 2001).
Learning and designing can be described at different levels of abstraction. Thus in Section 2, it is necessary to show that the activities of learning and design can be described at the knowledge level. In Section 3, a design activity is defined formally to show that associated with each design activity is the knowledge change that results from the activity. Section 4 describes briefly the five basic elements of a learning activity that was first presented in Sim and Duffy . Having characterised what the basic elements of a design activity and learning activity are the aim of Section 5 is to present a formalism to show the nature and manner in which design and learning activities can be coupled together. The discussion in Section 6 shows how the formalism proposed complements the dimensions proposed by Reich .
The J-form organisation (with a knowledge base that is collective and non- standardised) derives its capability from knowledge that is 'embedded' in its operating routines, team relationships and shared culture. Its archetypal features are best illustrated by some of the big knowledge-intensive Japanese firms (Nonaka and Takeuchi 1995; Aoki 1988). It combines the stability and efficiency of a bureaucracy with the flexibility and team dynamics of an adhocracy. One fundamental characteristic is that it allows an organic, non-hierarchical team structure to operate in parallel with its formal hierarchical managerial structure. Shared values and organisational culture form the environment where interaction across functions and divisions take place in a systematic manner. This is an adaptive and innovative form of organisation. It has a strong capacity to generate, diffuse and accumulate tacit knowledge continuously through ‘learning-by-doing’ and interaction. It is good at generating incremental and continuous innovation. However, learning in the J-form organization is also potentially conservative. Its stable social structure and shared knowledge base may block radical innovation.
The results indicate an average level of implementation of practices related to the structuring of organizational processes, although some are already applied by managers and present important results for the organization. It is concluded that the implementation of knowledge management practices, even if used intuitively and unsystematically by the managers of the schools investigated, can direct or present experiences to better use the intellectual capital involved. Under this approach and in accordance with the initially proposed objective of identifying the level of implementation of knowledge management practices aimed at structuring the organizational processes used by the public school manager, it is emphasized that they favor the integration of people in and out of school. They provide exchanges of experiences, dialogues, reflections and the involvement of everyone with school issues. The practices involved, Benchmarking; Best Practices; Organizational intelligence; Knowledge mapping; Management by competence; Bank of organizational competence; Bank of individual competences; Management of intellectual capital, whether for its purpose or through those involved, in some way, relate in the construction and sharing of knowledge.
Factors determining the healthcare waste management practice: This section tried to examine the effect of selected independent variables on healthcare waste management practice. The selected independent variables were adequate resource, healthcare HCWM guideline, HCWM plan, HCWM committee, hand washing facility, training, provision of personal protective equipment (PPE), types of service provision, and ownership of health institutions. In order to examine the relative importance or net effect of each independent variable, ordered logistic regression analysis was carried out. Before using the model, multicollinearity problem among the independent variables was tested using Contingency Coefficient. According to White (1980), іf the value of contingency coefficients іs greater than 0.75, the variables are said to be collinear. Consequently, the contingency coefficient result indicated that all the selected independent variables except HCWM committee and types of service provision had no Multicollinearity problem. As a result, type of service provision as one of the independent variables was excluded in the model and HCWM committee was included in the model. The national HCWM guideline says that all types of health institutions have to be established HCWM committee. And the study was considered this as inclusion criteria for HCWM committee.
Milton (2014) comprehends knowledge management as the means through which conveyance of the correct information, to fitting individuals, at the fortunate time, with the coveted piece and level of dynamics. The periods of the procedure that distinguish, create, convey and stay up with the latest the deliberately huge learning of the endeavor are of exceptional significance. This accumulation of exercisescannot be confined just to the data required at the very time however needs to guarantee the information source for the steady working of an association. Knowledge management as a key approach incorporates hierarchical structure, culture, learning maintenance, center abilities and outer systems. Entity structures control the way the entity is accorded knowledge, and the way personalities link up with each other. Extensively, there are two sorts of hierarchical structure, to be specific formal and casual (Meir, 2009). These two ideas are not autonomous, and the formal structure may incredibly impact casual systems, both decidedly and contrarily. Learning administration as a key device encourages the help of existing structures, capabilities, information maintenance, components, culture, and outer system and information administration frameworks (Yousif, 2013).
The nature of threads can be distinguished by the main concerns of the askers. These concerns are being used in the literature for the definition of question types [7, 9, 10]. Examples of question types are how-to-do- it – providing a scenario and asking how to imple- ment it—debug-corrective—dealing with problems in code already written —seeking-something—looking for some- thing objective (e.g., tutorial, tool, library) or subjective (e.g., an opinion, a suggestion, a recommendation)—and conceptual—regarding conceptual questions on a particu- lar topic (e.g., definition of concepts, best practices for a given technology). The definition itself of the how-to-do- it question type reveals that this type is more adherent to the purpose of documenting how to use API ele- ments. Nonetheless, questions of type debug-corrective are still useful as complementary documentation on how to fix frequent problems related to the usage of API elements, while the other types seems to be marginally useful.