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The value of knowledge sharing: impact of tacit and explicit knowledge sharing on team performance of scientists

The value of knowledge sharing: impact of tacit and explicit knowledge sharing on team performance of scientists

Externalization, on the other hand is a process of making tacit knowledge explicit. For example, organizations will try to capture what the employees know through creating platforms where they can interact and share knowledge, usually internal forums for communities of practice where they can exchange knowledge. Through synthesizing the body of knowledge, to some extent, but not fully will the process of externalization be successful. Early knowledge management practice and research have been mostly focused on managing explicit knowledge in forms of documents, forms, procedures and etc. creating huge repositories of knowledge and relying on IT to facilitate knowledge sharing processes, and enhance the collective memory of an organization However the assumption that when technology for knowledge sharing is implemented that employees will share knowledge is showed to be false, and often failed to make tacit knowledge explicit due to the cognitive nature of tacit knowledge (Pawlowski and Robey, 2004). Sharing of knowledge does not only depend on the technology factor but on many others. Furthermore, technology itself often fails to capture the most important component of knowledge, the tacit one. Our efforts are aimed at examining both sharing of tacit and explicit knowledge. We posit that sharing of information and codified knowledge facilitated by information technology, especially on the projects which are to some extent virtual, as well as tacit knowledge, ingrained in daily routines and embedded in people through the process of socialization are relevant for team performance. Based on this proposition we build our research model.
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Corrective Feedback and Second Language Acquisition: Differential Contributions of Implicit and Explicit Knowledge

Corrective Feedback and Second Language Acquisition: Differential Contributions of Implicit and Explicit Knowledge

The issue of error correction remains controversial in recent years due to the different positions of interface toward implicit and explicit knowledge of ESL learners. This study looks at the impacts of implicit corrective feedback in the form of recast on implicit and explicit knowledge of adult ESL learners. In an experimental study, lower-intermediate learners first were taught the grammatical features; then they completed communicative tasks during which the experimental group received recast and the control group received no feedback when an error occurred. Acquisition was measured by means of tests designed to measure implicit and explicit knowledge. Results of ANCOVA analysis revealed higher score for the experimental group; and result of t-test revealed that recast has significant effect on implicit knowledge. In line with the weak interface position toward implicit and explicit knowledge, the findings extend empirical support for Schmidt’s noticing hypothesis and function of recast in language learning.
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Effect of explicit and implicit FFI on EFL learners' implicit and explicit knowledge of simple and difficult morphosyntactic features

Effect of explicit and implicit FFI on EFL learners' implicit and explicit knowledge of simple and difficult morphosyntactic features

Some studies have attempted to compare the relative efficacy of explicit and implicit instruction (here FFI). Forty- nine of these studies which represented 98 instructional treatments were included in Norris and Ortega's (2000) meta- analytic research. In their study, the superiority of explicit types of L2 instruction over their implicit counterparts was empirically demonstrated. However, Norris and Ortega themselves and later Doughty (2003) discuss a number of important biases toward explicit knowledge in their studies that warrant caution in drawing any conclusive generalizations about the effectiveness of explicit versus implicit type of L2 instruction. Hence, the significance of studies attempting to probe this line of inquiry without any biases toward explicit knowledge and taking a balanced position toward both explicit and implicit types of L2 knowledge is clearly understood. 2.2 Interactions between Type of Language Form and Type of FFI
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Interference produces different forgetting rates for implicit and explicit knowledge

Interference produces different forgetting rates for implicit and explicit knowledge

Why would interference affect forgetting of implicit and explicit knowledge in the specific task used here and in Tunney (2003) in the first place? If it is assumed, for instance, that learning in the artificial grammar learning task consists, at least in part, of acquiring associations between consecutively typed manual responses, then any newly typed sequences of manual responses that do not correspond to the artificial grammar will weaken - absolutely and/or relative to other representations - the strengths of the acquired associations. In the real world, this interference might be due to the typing of any text on a typewriter or computer, for instance, to playing a piano, and the like.
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The effects of input enhancement and explicit instruction on developing Iranian lower-intermediate EFL learners’ explicit knowledge of passive voice

The effects of input enhancement and explicit instruction on developing Iranian lower-intermediate EFL learners’ explicit knowledge of passive voice

The results of the present study demonstrated superiority of explicit instruction group to both the enhanced input and control groups on both measures of explicit know- ledge. Additionally, in the case of UGJT, since input enhanced participants progressed better than their peers in control group, we can suggest that manipulation of written input was facilitative to induce short term improvement in the target structure and L2 development and consequently resulted progress in language learning. This finding in- dicates that learners exposed to some kind of intervention whether explicit or implicit were more successful than those who did not receive any kind of intervention. There- fore, making some linguistic forms more salient and noticeable to draw learners ’ attention to them can be effective in converting input into intake more significanly. Results also revealed the primacy of explicit instruction group over both the enhanced input and control groups, which indicate accelerating effect of explicit instruction in language learning and necessity of explicit instruction in the case of some language structures in EFL settings. The findings indicated that students were able to absorb selected grammatical forms when they were exposed to explicit instruction of rules and they showed sensitivity to ungrammatical forms in either grammatically judgment or metalinguistic knowledge tests. However, such a sensitivity to ungrammatical forms was not significantly attested in the input enhancement and control groups in MKT, it can be claimed that merely attracting learners ’ attention to a particular linguistic form (e.g., by bolding) does not appear to have a significant effect on learners’ explicit know- ledge. Overall, similar to Loewen and Reinders’s idea (2011) while implicit instruction can be beneficial, explicit instruction is often considered more effective. Therefore, material developers and language teachers should take into account that, at a general level, instruction regardless of its type can help progress language learning, suggesting a necessity for considering the ways language knowledge will be internalized in learners’ mind. Future studies are recommended to investigate the durability or long-term effects of explicit/implicit instructional approaches on explicit knowledge of EFL learners.
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Impact of explicit instruction on EFL learners’ implicit and explicit knowledge: A case of English relative clauses

Impact of explicit instruction on EFL learners’ implicit and explicit knowledge: A case of English relative clauses

Regarding the fact that the participants in this study benefited from explicit instruction to improve both their explicit and implicit knowledge, it can be claimed that the findings of this study may serve as an attempt to refute opposing ideas towards the effectiveness of explicit instruction. For instance, Krashen (1981, 1982, 1993) views explicit instruction to be effective in only simple structures and only in form of explicit knowledge. The results obtained here provide evidence that complex structures can be acquired through explicit instruction. Furthermore, as Loewen et al., (2009) stated, implicit learning did not result in either explicit or implicit knowledge, which can suggest the necessity of some form of explicit learning. Moreover, Krashen argues that the effects of explicit instruction are evident only if there are measures by which implicit knowledge is tested in free production tests and not in situations under monitoring and control. This is what Ellis (2005, 2009) is concerned with, i.e. lack of appropriate measures of implicit knowledge. Hence, using appropriate measures of both explicit, and more importantly, implicit knowledge in this study led to more reliable evidence to the effectiveness of explicit instruction in improving implicit knowledge.
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Explicit Form Focus Instruction: The Effects on Implicit and Explicit Knowledge of ESL Learners

Explicit Form Focus Instruction: The Effects on Implicit and Explicit Knowledge of ESL Learners

The debates over the efficiency of explicit FFI is in part owed to the difficulty of operationalizing procedural L2 knowledge or implicit language knowledge. Until recently, few studies evaluated L2 acquisition on communicative language ability, such as the capacity for fluent speech which is considered to be evidence of implicit language knowledge (Ellis, 2008). Implicit language knowledge is intuitive, and enables spontaneous use of the language characterized by fluency and control evident in our mother tongue or L1, and is considered to be procedural knowledge. By contrast, explicit knowledge is considered as conscious knowledge which may be verbally described (Ellis, 1994). Most of the studies in evaluating L2 acquisition have been conducted by assessing explicit knowledge rather than freely constructed responses hypothesized to tap into implicit procedural knowledge (N. Ellis, 2008; Norris & Ortega, 2000; Truscott, 1996, 1998). This measurement problem has been added to the debate concerning the effectiveness of explicit instruction (Hulstijn, 2005). Up to now, because of methodological difficulties in differentiating implicit and explicit knowledge few studies have addressed this issue (Akakura, 2009).
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The Case for Explicit Knowledge in Documents

The Case for Explicit Knowledge in Documents

In order to allow documents to be unambiguously inter- preted by both human readers and software agents, knowl- edge should be an explicit part of document representation. Rather than being the result of an imprecise, after-the-fact activity, knowledge elicitation in Semantic Web documents can be an exact, author-assisted process. However, instead of manifesting this additional responsibility as an extra pro- cess of annotation, knowledge elicitation can be an indistin- guishable part of the authoring process. In fact the knowl- edge elicitation process can actually help the author (or ed- itorial staff) rather than adding an extra burden, by provid- ing a synthesis of a range of targeted background material that would otherwise need to be searched for both manually and individually. This paper has introduced our contribu- tion to this process, WiCKOffice, a knowledge-writing envi- ronment. In the context of a project proposal writing sce- nario, WiCKOffice demonstrates that with a suitable set of ontologies and a supportive knowledge-aware environment, an author can be assisted in producing explicit knowledge documents.
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Formal Versus Informal Training & Tacit Versus Explicit Knowledge Sharing: What Matters More for the Entrepreneurially Oriented Firms?

Formal Versus Informal Training & Tacit Versus Explicit Knowledge Sharing: What Matters More for the Entrepreneurially Oriented Firms?

been previously reported in the literature (see for example; [103]) employees always have to borrow from tacit knowledge (skills or experiences) of their colleagues or search for explicit knowledge (institutionalized approaches or practices) existing in the company to better achieve innovative tasks. A large number of existing studies in the broader literature have stated that both the explicit and tacit components of organizational knowledge sharing practices play an important role in innovation (for a review see; [109,110,111]). Much of the most current writing on knowledge suggests that a firm‟s tacit knowledge is positively related to the ability to innovate, create value and identify opportunities ([112,113,114] ). Although the relationship between knowledge sharing and innovativeness has been widely discussed in the literature, few researches consider the specific effects that tacit and explicit knowledge sharing have on innovativeness. So this paper proposes the following hypotheses:
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Model Transfer with Explicit Knowledge of the Relation between Class Definitions

Model Transfer with Explicit Knowledge of the Relation between Class Definitions

This paper investigates learning methods for multi-class classification using labeled data for the target classification scheme and another la- beled data for a similar but different classi- fication scheme (support scheme). We show that if we have prior knowledge about the re- lation between support and target classification schemes in the form of a class correspondence table, we can use it to improve the model per- formance further than the simple multi-task learning approach. Instead of learning the in- dividual classification layers for the support and target schemes, the proposed method con- verts the class label of each example on the support scheme into a set of candidate class labels on the target scheme via the class cor- respondence table, and then uses the candi- date labels to learn the classification layer for the target scheme. We evaluate the proposed method on two tasks in NLP. The experimental results show that our method effectively learns the target schemes especially for the classes that have a tight connection to certain support classes.
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A Study of the Corporative Portals as a Tool of Explicit Knowledge Externalization in Universities

A Study of the Corporative Portals as a Tool of Explicit Knowledge Externalization in Universities

enormous variety and amount of information and knowledge, due to the multiplicity of their activities. This study aims to point out important aspects of the explicit knowledge expressed by the searched universities by the analysis of the content offered in their corporative portals. This is an exploratory study  made  through  direct  observation  of  the existing contents in the corporative portals of two public universities as well as three private ones. A comparative analysis of the existing contents in these portals was carried through; it can be useful to evaluate its use as factor of optimization of the generated explicit knowledge in the university. As results,  the  existence  of  important  differences could be verified in the composition and in the content of the corporative portals of the public universities compared to the private institutions. The main differences are about the kind of services and the destination of the information that have as focus different public-target. It could also be concluded that the searched private universities focus on the processes related to the attendance of the students, the support for the courses as well as  the  spreading  of  information  to  the  public interested in joining the institution; whereas the analyzed public universities prioritize more specific information, directed to the dissemination of the research developed internally or with institutional objectives.
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The use of tacit and explicit knowledge in public health: a qualitative study

The use of tacit and explicit knowledge in public health: a qualitative study

Within these frameworks are guidelines on different types of knowledge and evidence that should be used to inform decision-making throughout the planning pro- cess. Our review of public health planning models found that the emphasis in most models is on explicit knowl- edge. Sources of knowledge suggested include literature reviews, surveillance data, statistics from computerized patient records, key informant surveys, community for- ums and surveys, focus groups, mandates/guidelines for policies, and evaluations from other public health pro- grams [23-25,28,32,33]. These sources of evidence can be used for multiple steps in the planning process, such as the identification of a problem, identifying potential strategies to address the problem, deciding upon a parti- cular strategy, and evaluating the program. Tacit knowl- edge, on the other hand, is not referred to as a legitimate source of knowledge in planning frameworks, although there are opportunities for tacit knowledge to be used. Such opportunities could include determining stakeholder involvement and decision-making power, establishing program timing, determining resources available, assessing political agendas of others and the general political environment, assessing community readiness, and taking into account the local context [23,25-27]. Although planning frameworks identify these factors as important to consider, they do not provide clear guidance on how public health professionals should make these assessments, and make no sugges- tions on how to elicit tacit knowledge. The models that come closest to acknowledging tacit knowledge are the University of Toronto ’ s The Health Communication Unit (TCHU) Planning Model, which refers to previous experience as a source of evidence, and Ontario ’ s Health Planning Toolkit, which identifies expert opinion as a type of data [23,33].
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Effect of Explicit and Implicit Instruction on Implicit Knowledge of English past Simple Tense

Effect of Explicit and Implicit Instruction on Implicit Knowledge of English past Simple Tense

measured implicit knowledge. In the same vein, Ellis (2005) analyzed the measures used in the studies reviewed by Norris and Ortega (2000). He found that of 49 studies selected for review only 8 studies used implicit knowledge measure and the rest relied on discrete point or declarative knowledge-based tests which originally tap into explicit knowledge. To provide appropriate measures of these two types of knowledge, Ellis (2005) conducted a study using a principal component factor analysis, he found that (a) an oral imitation test, (b) an oral narration test, and(c) a timed grammatically judgment test load into implicit knowledge factor and (d) an untimed grammatically judgment test and (e) a meta-linguistic knowledge test into explicit knowledge. Since then few studies have been conducted on EI/II. Before moving on the literature review, looking into relationship between explicit and implicit knowledge seems necessary.
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Evaluating the Effectiveness of Explicit and Implicit Form-Focused Instruction on Explicit and Implicit Knowledge of EFL Learners

Evaluating the Effectiveness of Explicit and Implicit Form-Focused Instruction on Explicit and Implicit Knowledge of EFL Learners

Subsequent analyses explored the construct validity of the test instruments by means of a Principal Component Factor Analysis (SPSS Version16.0). The purpose was to see whether the four tests will reduce to two components according to predictions about the two knowledge types they predominantly measure. The scores for the four pre-tests were examined. An initial Principal Component Analysis extracted two components with an initial Eigenvalue of 2.018 and a second component with an Eigenvalue of 1.124, which together comprised 63.7% of the variance. As indicated by previous studies (e.g., R. Ellis, 2005, 2006) the OEIT and the Timed GJT loaded at 0.7 or higher on one factor (implicit knowledge) and the MKT and Untimed GJT loaded strongly (i.e., higher than 0.7) on factor 2 (explicit knowledge). The previous results present evidence in favor of separability of the two types of knowledge.
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Research on Explicit and Tacit Knowledge Interaction in Software Process Improvement Project

Research on Explicit and Tacit Knowledge Interaction in Software Process Improvement Project

fication of knowledge as either explicit or tacit is one of two prominent classifications in the knowledge manage- ment literature (Table 1 provides a brief overview of dif- ferent classifications of knowledge creation efforts [10]). Explicit knowledge is codified and documented, and its transfer can take place in impersonal ways—for in- stance, through written instructions and diagrams. Tacit knowledge is knowledge that is difficult to articulate, especially in terms of cause-effect relationships. It is context-specific, and is transferred mainly through social interactions [2]. Language is an excellent example of tacit knowledge: native speakers of a language are often unable to articulate the grammatical and syntactic rules governing it. Tacit knowledge contributes to the “sticki- ness” of information required for problem-solving, mak- ing it difficult for others to gather, transfer, and utilize. The difficult-to-codify nature of tacit knowledge con- tributes to difficult-to-imitate capabilities that may pro- vide competitive advantage to the organization. Success of process improvement projects depends on the capture of both explicit and tacit types of knowledge [10,11]. 2.3. Knowledge Enabling Software Process
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A DNA-based pattern classifier with in vitro learning and associative recall for genomic characterization and biosensing without explicit sequence knowledge

A DNA-based pattern classifier with in vitro learning and associative recall for genomic characterization and biosensing without explicit sequence knowledge

genomic information from biological samples without explicit knowledge of their genomic sequence or compos- ition (Figure 1). The idea of processing large amounts of information in a test tube, not on a conventional solid- state computer, presents the possibility of working with gDNA or cDNA on a community or population scale. The Biological Memory does not seek to determine the complete sequence information from biological samples. The Biological Memory is a laboratory protocol that, through DNA hybridization reactions with random probes, matches sequence patterns and stores the DNA sequence information in a DNA-based memory in vitro. Then, it matches or “recalls” the stored information based upon sequence similar- ity to new input (i.e., “associative recall”) [9]. Using a micro- array as an output method, read out is easily accomplished and high-throughput. Multiplexed detection is possible. More conventional techniques would access the genomic informa- tion in the biological samples with known sequences, and then, rely upon a digital computer for processing the data. Similarly, the massive volumes of short sequencing reads of NGS must be processed digitally for their de novo assembly. Pattern recognition and interpretation of large amounts of gene expression or genomic data are difficult problems for conventional computers. However, the Memory does all its information processing in vitro in one massively parallel step and does not require sequencing, not only alleviating sources of errors associated with sequencing techniques and in silico data processing, but also allowing the classification of patterns from all organisms in biological samples at the population or community scale. This paper discusses the theoretical ana- lysis of the microarray-based Biological Memory with DNA as a representative target and its experimental verification and optimization processes using gDNA from two model bacterial strains, i.e., Escherichia coli K12 and Bacillus subtilis, addressing basic understanding of the information processing capabilities of DNA, and the promises of the practical applications of those properties to biology and medicine.
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Differential Accessibility of Implicit and Explicit Grammatical Knowledge to EFL Learners' Language Proficiency

Differential Accessibility of Implicit and Explicit Grammatical Knowledge to EFL Learners' Language Proficiency

The distinction between implicit and explicit learning and knowledge has originated in cognitive psychology. In the first place, there has for long been much controversy in cognitive psychology over whether human cognition should be envisioned in the form of a unitary knowledge source capable of achieving different learning outcomes (Shanks, 2003) or as multiple, differentiated learning systems (Reber, 1976; Anderson, 1983; Anderson & Lebiere, 1998; Hazeltine & Ivry, 2003). In the second place, the controversy took a different form and direction within the camp of the proponents of distinct learning systems as how to theorize about the interplay between the functionally and neurally separate learning systems. Among different models of multiple learning systems in cognitive psychology, Anderson’s (1983, 1985) as well as Anderson and Lebiere’s ACT-R model has over the years been highly influential in shaping and directing L2 theory and research. Specifically, the ACT-R model’s argument for a dual knowledge system consisting of declarative knowledge (i.e., knowing that something is the case) and procedural knowledge (i.e., knowing how to do something) that are stored differently has been the impetus to the SLA studies dealing with implicit- explicit knowledge sources. The ACT-R model of human architecture posits a dual long-term memory system (declarative vs. procedural), besides the short-term working memory, that is at work processing, storing, and retrieving information. In this model, practice or repeated activation plays a central role in automatization and preceduralization of declarative knowledge.
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HELPING INTERNATIONAL TEACHING ASSISTANTS ACQUIRE DISCOURSE INTONATION: EXPLICIT AND IMPLICITL2 KNOWLEDGE

HELPING INTERNATIONAL TEACHING ASSISTANTS ACQUIRE DISCOURSE INTONATION: EXPLICIT AND IMPLICITL2 KNOWLEDGE

Abstract. This study explored a theoretically-driven permutation of an intervention designed to improve ITAs’ spoken Discourse Intonation (DI). The object was to learn if implicit knowledge growth in DI could be found as the result of an experimental group participating in explicit instruction and in audio-assisted repeated reading treatments using twice-weekly easy, popular science texts for 14 weeks. In a read-aloud condition where speech processing burdens were reduced, both an experimental and control group (who received explicit instruction only) improved over time on speech rate, planning pauses versus hesitation pauses, prominence, tone choices, and length of tone choice pause groups. In a free-response task where processing burdens were increased, however, there was little evidence of change in implicit knowledge of DI for the experimental group. One positive thing was learned: Explicit DI instruction did not reduce participants’ speech rate and thus participants could focus on form as well as meaning in extended speech. Explicit DI instruction, where form is linked to meaning, is worthwhile in that explicit knowledge may become proceduralized and available for learners’ extemporaneous use. Implicit knowledge building in DI, while difficult to demonstrate, may still be worthwhile if it builds learners’ knowledge of vocabulary (to improve prominence) and builds their experience hearing DI features linked to meaning within extended texts.
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Assessing the effect of focused direct and focused indirect written corrective feedback on explicit and implicit knowledge of language learners

Assessing the effect of focused direct and focused indirect written corrective feedback on explicit and implicit knowledge of language learners

Regarding the instruments used in this study, more research is needed to validate these instruments as measures of explicit and implicit knowledge. As Suzuki and DeKeyser (2017) highlighted, fine-grained measures of implicit and explicit knowledge are needed. Kim and Nam (2017) suggested that elicited imitation test is more valid in- strument for measuring implicit knowledge than timed grammaticality judgment test. Likewise, Tomita, Suzuki, and Jessop (2009) considered elicited imitation test as a valid measure of implicit knowledge. Further research can use elicited imitation test to meas- ure implicit knowledge which might yield different result. Using two new measures in- troduced by Suzuki (2017) and Vafaee, Suzuki, and Kachisnke (2017): self-paced reading task, word-monitoring task, visual-word task can result in different findings. Similarly, conducting this study in laboratory setting might have different results. Fur- thermore, future researchers should consider learners ’ zone of proximal development and scaffolding in WCF and choosing the target structure of the studies.
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A measurable approach for risk justification of explicit and tacit knowledge assessment

A measurable approach for risk justification of explicit and tacit knowledge assessment

Controlling knowledge management risks is one of the enterprise management tasks where managers and researchers focus on how to effectively evaluate risks when doing risk assessment (Yang & Gao, 2016). Risk assessment is a type of knowledge evaluation and whilst multiple models of knowledge evaluation have been proposed, a general conceptual framework is still lacking (Babik, Qian, Singh, & Ford, 2014). Without such a general framework, presenting knowledge-associated risks in a way that risk managers can appreciate is a particular challenge. We propose an approach for measuring and assessing the risks related to tacit and explicit knowledge as well as knowledge management within organizations. The approach converts identified risks into financial values that are more concrete for management and proposes possible solutions to mitigate the identified risks.
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