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Journal articles on the topic 'Explicit knowledge'

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Published: 4 June 2021

Last updated: 20 February 2023

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1

Zhang, Wusheng. "Harnessing Explicit Knowledge." Journal of Economics and Behavioral Studies 2, no. 3 (March 15, 2011): 97–107. http://dx.doi.org/10.22610/jebs.v2i3.227.

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In the search for sustainable competitive advantage, managing knowledge is critical not only for large organizations but also for Small and Medium sized Tourism Enterprises (SMTEs) where limited resources and the lack of the strategic direction are prevalent. Findings from the literature review suggest that, in relative terms, SMTEs are less ready for implementing knowledge management projects than are large organizations. It is also suggested that SMTEs are in need of practical strategic guidance if they are to make the most of the, often under-exploited, knowledge within and available to their organizations. For the support of SMTEsâ€™ initial needs for knowledge management, this paper proposes a strategy aimed at harnessing explicit knowledge and strategic activities based on an extensive analysis of the literature. The proposed strategy contains actionable steps with timelines and milestones that can be implemented and modified iteratively by SMTEs, with in-built assessment and measurement mechanisms. The results of our study suggest that implementation itself can be flexible as well as iterative with no need for all the steps outlined for an improvement of the knowledge management process to be followed.

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2

Al-Shawabkeh, Abdallah, and Rama Kanungo. "Credit risk estimate using internal explicit knowledge." Investment Management and Financial Innovations 14, no. 1 (March 31, 2017): 55–66. http://dx.doi.org/10.21511/imfi.14(1).2017.06.

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Jordanian banks traditionally use a set of indicators, based on their internal explicit knowledge to examine the credit risk caused by default loans of individual borrowers. The banks are reliant on the personal and financial information of the borrowers, obtained by knowing them, often referred as internal explicit knowledge. Internal explicit knowledge characterizes both financial and non-financial indicators of individual borrowers, such as; loan amount, educational level, occupation, income, marital status, age, and gender. The authors studied 2755 default or non-performing personal loan profiles obtained from Jordanian Banks over a period of 1999 to 2014. The results show that low earning unemployed borrowers are very likely to default and contribute to non-performing loans by increasing the chances of credit risk. In addition, it is found that the unmarried, younger borrowers and moderate loan amount increase the probability of non-performing loans. On the contrary, borrowers employed in private sector and at least educated to a degree level are most likely to mitigate the credit risk. The study suggests improving the decision making process of Jordanian banks by making it more quantitative and dependable, instead of using only subjective or judgemental based understanding of borrowers.

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3

MURATA, Yoshimi. "From Tacit Knowledge to Explicit Knowledge." Journal of the Society of Mechanical Engineers 118, no. 1156 (2015): 134–35. http://dx.doi.org/10.1299/jsmemag.118.1156_134.

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4

Mercado, Eduardo, and Scott O. Murray. "Explicit knowledge in dolphins?" Behavioral and Brain Sciences 22, no. 5 (October 1999): 774–75. http://dx.doi.org/10.1017/s0140525x99442189.

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The theoretical framework proposed by Dienes & Perner sets the wrong standards for knowledge to be considered explicit. Animals other than humans possess knowledge, too, some of which is probably explicit. We argue that a comparative approach to investigating knowledge is likely to be more fruitful than one based on linguistic constructs and unobservable phenomena.

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5

Ramanujam, R. "View-based explicit knowledge." Annals of Pure and Applied Logic 96, no. 1-3 (March 1999): 343–68. http://dx.doi.org/10.1016/s0168-0072(98)00045-1.

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6

Návrat, Pavol, and Viera Rozinajová. "Making programming knowledge explicit." Computers & Education 21, no. 4 (November 1993): 281–99. http://dx.doi.org/10.1016/0360-1315(93)90032-e.

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7

Dienes, Zoltan, and Josef Perner. "A theory of implicit and explicit knowledge." Behavioral and Brain Sciences 22, no. 5 (October 1999): 735–808. http://dx.doi.org/10.1017/s0140525x99002186.

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The implicit-explicit distinction is applied to knowledge representations. Knowledge is taken to be an attitude towards a proposition which is true. The proposition itself predicates a property to some entity. A number of ways in which knowledge can be implicit or explicit emerge. If a higher aspect is known explicitly then each lower one must also be known explicitly. This partial hierarchy reduces the number of ways in which knowledge can be explicit. In the most important type of implicit knowledge, representations merely reflect the property of objects or events without predicating them of any particular entity. The clearest cases of explicit knowledge of a fact are representations of one's own attitude of knowing that fact. These distinctions are discussed in their relationship to similar distinctions such as procedural-declarative, conscious-unconscious, verbalizable-nonverbalizable, direct-indirect tests, and automatic-voluntary control. This is followed by an outline of how these distinctions can be used to integrate and relate the often divergent uses of the implicit-explicit distinction in different research areas. We illustrate this for visual perception, memory, cognitive development, and artificial grammar learning.

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8

Hugo-Burrows, M. M. "Converting tacit knowledge into explicit knowledge in organisations." Communicare: Journal for Communication Studies in Africa 21, no. 1 (October 31, 2022): 61–81. http://dx.doi.org/10.36615/jcsa.v21i1.1830.

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Business organisations are increasingly viewing knowledge as their most valuable andstrategic resource to remain competitive. Every organisation has both explicit knowledge,referring to carefully analysed and defined knowledge, and tacit knowledge, referringto complex knowledge, difficult to specify and often unrecorded. Tacit knowledgebecomes embedded in an individual's personal expertise and cannot be expressed throughthe normal use of words. But it is precisely the tacit knowledge that often delivers asustainable competitive advantage, as it is this part that competitors have difficultyin replicating. Many organisations are realizing that they must explicitly manage their knowledgeresources and capabilities, and they have initiated a range of knowledge managementprogrammes. An important managerial responsibility resides in managing the knowledgetransfercontext, including the assessment of all knowledge possessed by a firm. Thisnecessitates the conversion of tacit knowledge into explicit knowledge. This article looks at the tacit knowledge literature and focuses on the existing methods of converting tacit knowledge into implicit knowledge in organisations. A pilot surveyon existing tacit knowledge articulation in a large South African province is discussed.This has pointed towards a more comprehensive research project, with the aim ofproviding a model for tacit knowledge communication strategies in South Africanmulticultural firms.

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9

VanPatten, Bill. "Why Explicit Knowledge Cannot Become Implicit Knowledge." Foreign Language Annals 49, no. 4 (November 4, 2016): 650–57. http://dx.doi.org/10.1111/flan.12226.

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10

Cairó Battistutti, Osvaldo, and Dominik Bork. "Tacit to explicit knowledge conversion." Cognitive Processing 18, no. 4 (July 4, 2017): 461–77. http://dx.doi.org/10.1007/s10339-017-0825-6.

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11

Mealor, Andy D., and Zoltan Dienes. "Explicit feedback maintains implicit knowledge." Consciousness and Cognition 22, no. 3 (September 2013): 822–32. http://dx.doi.org/10.1016/j.concog.2013.05.006.

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12

van Ditmarsch, Hans, Tim French, Fernando R. Velázquez-Quesada, and Yì N. Wáng. "Implicit, explicit and speculative knowledge." Artificial Intelligence 256 (March 2018): 35–67. http://dx.doi.org/10.1016/j.artint.2017.11.004.

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13

Han, Y., and R. Ellis. "Implicit knowledge, explicit knowledge and general language proficiency." Language Teaching Research 2, no. 1 (January 1, 1998): 1–23. http://dx.doi.org/10.1191/136216898672061211.

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14

Herschel, Richard T., Hamid Nemati, and David Steiger. "Tacit to explicit knowledge conversion: knowledge exchange protocols." Journal of Knowledge Management 5, no. 1 (March 2001): 107–16. http://dx.doi.org/10.1108/13673270110384455.

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15

Han, Youngju, and Rod Ellis. "Implicit knowledge, explicit knowledge and general language proficiency." Language Teaching Research 2, no. 1 (January 1998): 1–23. http://dx.doi.org/10.1177/136216889800200102.

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16

Vokey, John R., and Philip A. Higham. "Implicit knowledge as automatic, latent knowledge." Behavioral and Brain Sciences 22, no. 5 (October 1999): 787–88. http://dx.doi.org/10.1017/s0140525x99582186.

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Implicit knowledge is perhaps better understood as latent knowledge so that it is readily apparent that it contrasts with explicit knowledge in terms of the form of the knowledge representation, rather than by definition in terms of consciousness or awareness. We argue that as a practical matter any definition of the distinction between implicit and explicit knowledge further involves the notion of control.

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17

Obrenovic, Bojan, Slobodan Obrenovic, and Akmal Hudaykulov. "The value of knowledge sharing: impact of tacit and explicit knowledge sharing on team performance of scientists." International Journal of Management Science and Business Administration 1, no. 2 (2015): 33–52. http://dx.doi.org/10.18775/ijmsba.1849-5664-5419.2014.12.1003.

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Knowledge sharing that takes place among team members is a process of great relevance that builds ties and relationships which in turn results in positive organizational and team outcomes. However, as it is not usually formally included in the job descriptions and is not a formal part of organizations’ and team activities, it is considered to be an organization citizenship behavior. Our paper emphasizes significance of tacit and explicit knowledge sharing to team performance in the context of scientific cooperation. Positive relationship between tacit knowledge sharing and explicit knowledge sharing with team performance was found using linear regression. Furthermore, high levels of knowledge sharing and team performance were identified among scientists.

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18

Willingham, Daniel B., and Kelly Goedert-Eschmann. "The Relation Between Implicit and Explicit Learning: Evidence for Parallel Development." Psychological Science 10, no. 6 (November 1999): 531–34. http://dx.doi.org/10.1111/1467-9280.00201.

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Much research has focused on the separability of implicit and explicit learning, but less has focused on how they might interact. A recent model suggests that in the motor-skill domain, explicit knowledge can guide movement, and the implicit system learns in parallel, based on these movements. Functional imaging studies do not support that contention, however; they indicate that learning is exclusively implicit or explicit. In the experiment reported here, participants learned a motor sequencing task either implicitly or explicitly. At transfer, most of the stimuli were random, but the sequence occasionally appeared; thus, it was not obvious that explicit knowledge could be applied to the task. Nevertheless, participants with explicit training showed sequence knowledge equivalent to those with implicit training, implying that implicit knowledge had been acquired in parallel with explicit knowledge. This result has implications for the development of automaticity and of motor-skill learning.

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19

Archibald, Tom, Jeanne Peiffer, and Norbert Schappacher. "Explicit Versus Tacit Knowledge in Mathematics." Oberwolfach Reports 9, no. 1 (2012): 131–210. http://dx.doi.org/10.4171/owr/2012/04.

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20

Witzel, Andreas, Jonathan Zvesper, and Ethan Kennerly. "Explicit Knowledge Programming for Computer Games." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 4, no. 1 (September 27, 2021): 138–43. http://dx.doi.org/10.1609/aiide.v4i1.18686.

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The main aim of this paper is to raise awareness of higher-order knowledge (knowledge about someone else's knowledge) as an issue for computer game AI. We argue that a number of existing game genres, especially those involving social interaction, are natural fields of application for an approach we call explicit knowledge programming. We motivate the use of this approach, and describe a simple implementation based upon it. A survey of recent literature and computer games illustrates its novelty.

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21

Agassi, Joseph. "Book Review: Tacit and Explicit Knowledge." Philosophy of the Social Sciences 43, no. 2 (May 10, 2013): 275–79. http://dx.doi.org/10.1177/0048393111400704.

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22

Meulemans, Thierry. "Explicit Knowledge in Artificial Grammar Learning." Psychologica Belgica 42, no. 3 (January 1, 2002): 213. http://dx.doi.org/10.5334/pb.995.

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23

Carroll, Jane, Gail Gillon, and Brigid McNeill. "Explicit Phonological Knowledge of Educational Professionals." Asia Pacific Journal of Speech, Language and Hearing 15, no. 4 (December 2012): 231–44. http://dx.doi.org/10.1179/136132812804731820.

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24

Roehr, Karen. "Explicit knowledge and learning in SLA." AILA Review 23 (December 9, 2010): 7–29. http://dx.doi.org/10.1075/aila.23.02roe.

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SLA researchers agree that explicit knowledge and learning play an important role in adult L2 development. In the field of cognitive linguistics, it has been proposed that implicit and explicit knowledge differ in terms of their internal category structure and the processing mechanisms that operate on their representation in the human mind. It has been hypothesized that linguistic constructions which are captured easily by metalinguistic descriptions can be learned successfully through explicit processes, resulting in accurate use. However, increased accuracy of use arising from greater reliance on explicit processing may lead to decreased fluency. Taking these hypotheses as a starting point, I present a case study of an adult L2 learner whose development of oral proficiency was tracked over 17 months. Findings indicate that explicit knowledge and learning have benefits as well as limitations. Use of metalinguistic tools was associated with increased accuracy; moreover, there was no obvious trade-off between accuracy and fluency. At the same time, resource-intensive explicit processing may impose too great a cognitive load in certain circumstances, apparently resulting in implicit processes taking over. I conclude that explicit and implicit knowledge and learning should be considered together in order to gain a full understanding of L2 development.

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25

Bowles, Melissa A. "MEASURING IMPLICIT AND EXPLICIT LINGUISTIC KNOWLEDGE." Studies in Second Language Acquisition 33, no. 2 (May 6, 2011): 247–71. http://dx.doi.org/10.1017/s0272263110000756.

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Although claims about explicit and implicit language knowledge are central to many debates in SLA, little research has been dedicated to measuring the two knowledge types (R. Ellis, 2004, 2005). The purpose of this study was to validate the use of the battery of tests reported in Ellis (2005) to measure implicit and explicit language knowledge. Whereas Ellis (2005) tested only second-language (L2) learners (of English), this study tested both L2 and heritage language (HL) learners (of Spanish). Results showed that test scores loaded on a two-factor model, as in Ellis (2005), thereby providing construct validity for the tests, on a population of HL learners who have little explicit knowledge by virtue of the environment in which they acquired Spanish.

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26

Abu-Hanna, A., and W. Jansweijer. "Modeling domain knowledge using explicit conceptualization." IEEE Expert 9, no. 5 (October 1994): 53–64. http://dx.doi.org/10.1109/64.331490.

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27

Warde, Alan. "Book Review: Tacit and Explicit Knowledge." Sociological Review 58, no. 4 (November 2010): 714–16. http://dx.doi.org/10.1111/j.1467-954x.2010.01954.x.

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28

Hu, Jhyfang, and Jerzy W. Rozenblit. "Knowledge acquisition based on explicit representation." Expert Systems with Applications 3, no. 3 (January 1991): 303–15. http://dx.doi.org/10.1016/0957-4174(91)90054-i.

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29

Akanmu, Semiu A., and Zulikha Jamaludin. "Students' Data-Driven Decision Making in HEI: The Explicit Knowledge Involved." International Journal of Information and Education Technology 6, no. 1 (2016): 71–75. http://dx.doi.org/10.7763/ijiet.2016.v6.661.

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30

Zhyriakova, I. A., and S. V. Holub. "A new approach to the formal explicit specification of knowledge acquisition." Mathematical machines and systems 4 (2019): 139–45. http://dx.doi.org/10.34121/1028-9763-2019-4-139-145.

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31

Indriani, Made Novia, I. Nyoman Arya Thanaya, Nyoman Yudha Astana, and A. A. Gde Agung Yana. "Knowledge Sharing In Perspective Of Tri Kaya Parisudha And Its Effect On Value Engineering Construction Projects." International Journal of Engineering and Emerging Technology 5, no. 1 (July 28, 2020): 61. http://dx.doi.org/10.24843/ijeet.2020.v05.i01.p12.

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Abstract Knowledge is the implementation of information and is convinced can be used for decision making. In this 21st century the success of an organization depends very much on the knowledge they have and how to utilize existing knowledge. The objectives of the research are to know and understand the effect of tacit knowledge and explicit knowledge in the Tri kaya Parisudha perspective on the value engineering of construction projects and to know and understand the influence of explicit knowledge mediating the relationship of tacit knowledge to the value engineering of construction projects. Quantitative analysis used is multivariate analysis using structural equation modeling or SEM with a variance-based or component-based approach called PLS (Partial Least Square). Tacit knowlege in manacika perspective significantly influences explicit knowledge in wacika and kayika perspectives, as well as tacit knowlege and explicit knowledge in manacika, wacika and kayika perspectives significantly influence construction project value engineering. Whereas explicit knowledge partially mediates between tacit knowledge to value engineering on construction project. Index Terms— Knowledge sharing, Tri Kaya Parisudha, Value engineering, Construction projects.

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32

Tamayo, Ricardo, and Peter A. Frensch. "Temporal Stability of Implicit Sequence Knowledge." Experimental Psychology 62, no. 4 (September 2015): 240–53. http://dx.doi.org/10.1027/1618-3169/a000293.

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Abstract. Previous research has shown that explicit and implicit knowledge of artificial grammars may decay at different rates (e.g., Tamayo & Frensch, 2007 ; Tunney, 2003 ). We extend these findings to sequential regularities embedded in serial reaction time (SRT) tasks. We compared the forgetting patterns of implicit and explicit knowledge after a retention interval of 7 days without rehearsal. Explicit knowledge decayed after 7 days, whereas implicit knowledge was retained. These data were modeled according to the assumptions involved in the single-system model suggested by Shanks, Wilkinson, and Channon (2003) . The best fit for the model was obtained by modifying the parameters related to (a) the common knowledge-strength variable for implicit and explicit knowledge, and (b) reliability of the explicit test. We interpret these dissociations as a boundary condition for single-system models that assume constant random noise to explain dissociations in the forgetting patterns of implicit and explicit sequential knowledge.

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33

Akakura, Motoko. "Evaluating the effectiveness of explicit instruction on implicit and explicit L2 knowledge." Language Teaching Research 16, no. 1 (December 12, 2011): 9–37. http://dx.doi.org/10.1177/1362168811423339.

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34

OTT, Margus. "Confucius’ Embodied Knowledge." Asian Studies 5, no. 2 (June 30, 2017): 65–85. http://dx.doi.org/10.4312/as.2017.5.2.65-85.

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The main purpose of the present article is to explicitly link the Analects to the embodiment theory (ET). As indicated in the introduction, embodiment has been an important topic in recent Sinological research, but until now rather few explicit connections have been made with the ET. In relation to the embodied knowledge, the article discusses the following topics: embodiment, embeddedness, enactment, extendedness, emotivity, implicitness, emergence, joy and apprenticeship or self-cultivation. The same themes are found to be important in the Analects, with a plethora of examples. Arguably ET could thus be a useful paradigm for discussing several important themes of the Analects. And the Analects being one of the founding texts of the Chinese philosophical tradition (though similar concerns are manifest also in other texts), it could also be beneficial to further developments in the ET itself, on the condition that its proponents familiarize themselves with the Chinese philosophical tradition where important issues of ET have been explicitly discussed for two and a half millennia.

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35

SUZUKI, YUICHI. "Validity of new measures of implicit knowledge: Distinguishing implicit knowledge from automatized explicit knowledge." Applied Psycholinguistics 38, no. 5 (May 9, 2017): 1229–61. http://dx.doi.org/10.1017/s014271641700011x.

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ABSTRACTAccumulating evidence suggests that time-pressured form-focused tasks like grammaticality judgment tests (GJTs) can measure second language (L2) implicit knowledge. The current paper, however, proposes that these tasks draw on automatized explicit knowledge. A battery of six grammar tests was designed to distinguish automatized explicit knowledge and implicit knowledge. While three time-pressured form-focused tasks (an auditory GJT, a visual GJT, and a fill in the blank test) were hypothesized to measure automatized explicit knowledge, three real-time comprehension tasks (a visual-world task, a word-monitoring task, and a self-paced reading task) were hypothesized to measure implicit knowledge. One hundred advanced L2 Japanese learners with first language Chinese residing in Japan took all six tests. Confirmatory factor analysis and multitrait-multimethod analysis provided an array of evidence supporting that these tests assessed two types of linguistic knowledge separately with little influence from the method effects. The results analyzed separately by length of residence in Japan (a proxy for the amount of naturalistic L2 exposure) showed that learners with longer residence in Japan can draw on implicit knowledge in the real-time comprehension tasks with more stability than those with shorter residence. These findings indicate the potential of finely tuned real-time comprehension tasks as measures of implicit knowledge.

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36

Knee, Robert, Sean Thomason, James Ashe, and Daniel T. Willingham. "The representation of explicit motor sequence knowledge." Memory & Cognition 35, no. 2 (March 2007): 326–33. http://dx.doi.org/10.3758/bf03193453.

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37

Chilton, Michael A., and James M. Bloodgood. "The Dimensions of Tacit & Explicit Knowledge." International Journal of Knowledge Management 4, no. 2 (April 2008): 75–91. http://dx.doi.org/10.4018/jkm.2008040106.

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38

Acar, William, Alan T. Burns, and Pratim Datta. "Explicit Knowledge Transfers in New Product Development." International Journal of Strategic Decision Sciences 5, no. 4 (October 2014): 16–50. http://dx.doi.org/10.4018/ijsds.2014100102.

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The literature on learning in new product development (NPD) documents the processes globally but is short on specifics. Knowledge levels are not clearly conceptualized, nor are there clear devices for documenting knowledge transfers in terms of knowledge levels. This paper presents the methods of a qualitative research approach for measuring knowledge transfer directly in terms of knowledge. The paper specifically addresses the commonly avoided dimension of knowledge, depth. The methods are derived from a real-life comparative case study exploring knowledge sharing in product development. Our focused interview approach has been refined to avoid unproductive digressions by the subjects and certain forms of bias, yet still obtain rich accounts of project events. Evidence of transfer obtained by the interviews is analysed in terms of three knowledge dimensions: scope, depth and action. Methods for aggregating and interpreting data are discussed and an operational flowchart for knowledge transfer coding is proposed.

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39

Flanagan, Jane. "Nursing Knowledge Development: Making the Implicit, Explicit." International Journal of Nursing Knowledge 30, no. 2 (April 2019): 67. http://dx.doi.org/10.1111/2047-3095.12245.

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40

Hudson, Peter, Rebecca Spooner-Lane, and Michelle Murray. "Making mentoring explicit: articulating pedagogical knowledge practices." School Leadership & Management 33, no. 3 (July 2013): 284–301. http://dx.doi.org/10.1080/13632434.2012.724673.

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41

Bijker, Wiebe E. "Tacit and Explicit Knowledge (review)." Technology and Culture 52, no. 4 (2011): 809–10. http://dx.doi.org/10.1353/tech.2011.0164.

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42

Andringa, Sible, and Maja Curcic. "HOW EXPLICIT KNOWLEDGE AFFECTS ONLINE L2 PROCESSING." Studies in Second Language Acquisition 37, no. 2 (May 20, 2015): 237–68. http://dx.doi.org/10.1017/s0272263115000017.

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Form-focused instruction studies generally report larger gains for explicit types of instruction over implicit types on measures of controlled production. Studies that used online processing measures—which do not readily allow for the application of explicit knowledge—however, suggest that this advantage occurs primarily when the target structure is similar in the first language (L1) and the second language (L2). This study investigated how explicit knowledge of a structure that does not exist in the L1 affects the initial stage of adult L2 acquisition. Fifty-one Dutch L1 speakers received a short auditory exposure (instruction) to a new language that included differential object marking (DOM), in which animate but not inanimate direct objects are preceded by a preposition. For 26 learners, the instruction was complemented by a brief rule explanation. Afterward, learners’ online processing and explicit knowledge of DOM were measured by means of eye-tracking (visual world paradigm) and oral grammaticality judgments. Results show that metalinguistic information promoted learners’ performance on the grammaticality judgment task. Although differences between the groups were also found on the eye-tracking measure, learners were not able to use DOM to predict the following object.

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43

ROGERS, JOHN, ANDREA RÉVÉSZ, and PATRICK REBUSCHAT. "Implicit and explicit knowledge of inflectional morphology." Applied Psycholinguistics 37, no. 4 (July 21, 2015): 781–812. http://dx.doi.org/10.1017/s0142716415000247.

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ABSTRACTThis study set out to test the degree to which second language inflectional morphology can be acquired as a result of incidental exposure and whether the resulting knowledge is implicit (unconscious) or explicit (conscious) in nature. Participants were exposed to an artificial language system based on Czech morphology under incidental learning conditions. In the testing phase, a grammaticality judgment test was utilized to assess learning. In addition, subjective measures of awareness and retrospective verbal reports were used to measure whether the acquired knowledge was conscious or not. The results of the experiment indicate that participants can rapidly develop knowledge of second language inflectional morphology under incidental learning conditions in the absence of verbalizable rule knowledge.

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44

Wyatt, Jeremy C. "10. Management of explicit and tacit knowledge." Journal of the Royal Society of Medicine 94, no. 1 (January 2001): 6–9. http://dx.doi.org/10.1177/014107680109400102.

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45

VAN DER HOEK, W., and J. J. CH MEYER. "MAKING SOME ISSUES OF IMPLICIT KNOWLEDGE EXPLICIT." International Journal of Foundations of Computer Science 03, no. 02 (June 1992): 193–223. http://dx.doi.org/10.1142/s0129054192000139.

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We discuss issues of expressibility and completeness of the logic of implicit knowledge (I) and “everybody’s knowledge” (E), as introduced in a system with a number m of epistemic agents by Halpern & Moses. The operator E is defined as a conjunction and corresponds semantically to the union of the m accessibility relations. Dually, the operator I is semantically associated with an intersection, but it is, surprisingly, not equivalent with a disjunction. From the view of Kripke structures there is a related asymmetry: although union can be modally defined, intersection cannot! We discuss consequences (in terms of (in)expressibility, correspondence and completeness) of this property for the epistemic logic under consideration and also present an extension of modal logic in which intersection is expressible.

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46

Brezhnev, Vladimir, and Roman Kuznets. "Making knowledge explicit: How hard it is." Theoretical Computer Science 357, no. 1-3 (July 2006): 23–34. http://dx.doi.org/10.1016/j.tcs.2006.03.010.

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47

Ribeiro, Rodrigo. "Remarks on explicit knowledge and expertise acquisition." Phenomenology and the Cognitive Sciences 12, no. 2 (July 14, 2012): 431–35. http://dx.doi.org/10.1007/s11097-012-9268-9.

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48

Addis, Mark. "Tacit and explicit knowledge in construction management." Construction Management and Economics 34, no. 7-8 (May 10, 2016): 439–45. http://dx.doi.org/10.1080/01446193.2016.1180416.

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Desouza, Kevin C., Yukika Awazu, and Yun Wan. "Factors governing the consumption of explicit knowledge." Journal of the American Society for Information Science and Technology 57, no. 1 (2005): 36–43. http://dx.doi.org/10.1002/asi.20250.

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Herschel, Richard, Hamid Nemati, and David Steiger. "Knowledge Exchange Protocols: A Second Study." Journal of Information & Knowledge Management 02, no. 02 (June 2003): 153–63. http://dx.doi.org/10.1142/s0219649203000085.

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Abstract:

In the knowledge management domain, the conversion of tacit knowledge to explicit knowledge is critical because it is a prerequisite to the knowledge amplification process wherein knowledge becomes part of an organization's knowledge network. Moreover, this process is strategically important because it enhances an organization's ability to create new knowledge that is inevitably expressed through the organization's capabilities, products, and services. The conversion of tacit to explicit knowledge is particularly relevant to information technology (IT), because IT can only partially facilitate tacit knowledge management, while it offers a substantial number of techniques to support the management and sharing of explicit knowledge. In this paper, knowledge exchange protocols are examined as a vehicle for improving the tacit-to-explicit knowledge conversion process. In a second experiment testing the use of knowledge exchange protocols, initial findings are confirmed: while structure may significantly improve the tacit-to-explicit knowledge conversion process, it also matters how the structure is employed in this process.

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