{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T12:14:56Z","timestamp":1766578496313,"version":"3.41.2"},"reference-count":32,"publisher":"Emerald","issue":"5","license":[{"start":{"date-parts":[[2013,9,9]],"date-time":"2013-09-09T00:00:00Z","timestamp":1378684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,9,9]]},"abstract":"<jats:sec>\n               <jats:title content-type=\"abstract-heading\">Purpose<\/jats:title>\n               <jats:p> \u2013 <jats:italic>The paper aims to provide a methodology by which organisational knowledge can be extracted and visualised dynamically over time, providing a glimpse into the knowledge evolution processes that occur within organisations.<\/jats:italic> \n               <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title>\n               <jats:p> \u2013 <jats:italic>Recursive analysis of email interactions is offered as a case to account for the knowledge structure evolution related to the different programs of international non-governmental organization (INGO). Several methods are used: analysis of the network expansion to see whether the process is random or uniform is performed, visualisation of the network configuration changes throughout studied time period; and the statistical examination of network formation.<\/jats:italic> \n               <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Findings<\/jats:title>\n               <jats:p> \u2013 <jats:italic>The results of the presented study indicate that content structure of electronic knowledge networks exhibits hierarchical and centralised tendencies. The social network analysis results suggest that INGO exhibits non-hierarchical and decentralized structure of the individuals contributing to the discussion lists.<\/jats:italic> \n               <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Research limitations\/implications<\/jats:title>\n               <jats:p> \u2013 <jats:italic>By providing the means to carry out network evolution analysis of content structure dynamics and social interactions, the presented work provides a means for probabilistically modelling patterns of organisational knowledge evolution.<\/jats:italic> \n               <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Practical implications<\/jats:title>\n               <jats:p> \u2013 <jats:italic>The approach allows the exploration of the dynamics of tacit to explicit knowledge, from individual to the group and from informal groups to the whole organisation.<\/jats:italic> \n               <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title>\n               <jats:p> \u2013 <jats:italic>By displaying the large collection of the key phrases that reflected the evolution of the organisational knowledge structure over the time, organisational emails are placed in meaningful context explaining the language of the organisation and context of knowledge structure evolution.<\/jats:italic>\n               <\/jats:p>\n            <\/jats:sec>","DOI":"10.1108\/jkm-02-2013-0058","type":"journal-article","created":{"date-parts":[[2013,9,19]],"date-time":"2013-09-19T13:05:43Z","timestamp":1379595943000},"page":"724-740","source":"Crossref","is-referenced-by-count":23,"title":["Visualisation of the organisation knowledge structure evolution"],"prefix":"10.1108","volume":"17","author":[{"given":"Mario","family":"\u0160torga","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ali","family":"Mostashari","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tino","family":"Stankovi\u0107","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2022012720162424900_b1","doi-asserted-by":"crossref","unstructured":"Ahuja, M.K.\n                and \n                  Carley, K.M.\n                (1998), \u201cNetwork structure in virtual organizations\u201d, Journal of Computer-Mediated Communications, Vol. 3 No. 4.","DOI":"10.1111\/j.1083-6101.1998.tb00079.x"},{"key":"key2022012720162424900_b2","doi-asserted-by":"crossref","unstructured":"Ahuja, M.K.\n               , \n                  Galletta, D.\n                and \n                  Carley, 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Sharpe, Inc., Armonk, NY."},{"key":"key2022012720162424900_b8","unstructured":"Fry, B.J.\n                (2008), Visualizing Data, O'Reilly Media, Inc., Sebastopol, CA."},{"key":"key2022012720162424900_b9","doi-asserted-by":"crossref","unstructured":"Jones, Q.\n               , \n                  Ravid, G.\n                and \n                  Rafaeli, S.\n                (2004), \u201cInformation overload and the message dynamics of online interaction spaces: a theoretical model and empirical exploration\u201d, Information Systems Research, Vol. 15 No. 2, pp. 194-210.","DOI":"10.1287\/isre.1040.0023"},{"key":"key2022012720162424900_b10","doi-asserted-by":"crossref","unstructured":"Mano, R.S.\n                and \n                  Mesch, G.S.\n                (2010), \u201cEmail characteristics, work performance and distress\u201d, Computers in Human Behavior, Vol. 26 No. 1, pp. 61-69.","DOI":"10.1016\/j.chb.2009.08.005"},{"key":"key2022012720162424900_b11","doi-asserted-by":"crossref","unstructured":"Medelyan, O.\n                and \n                  Witten, I.H.\n                (2008), \u201cDomain independent automatic key phrase indexing with small training sets\u201d, Journal of American Society for Information Science and Technology, Vol. 59 No. 7, pp. 1026-1040.","DOI":"10.1002\/asi.20790"},{"key":"key2022012720162424900_b12","doi-asserted-by":"crossref","unstructured":"Medelyan, O.\n               , \n                  Frank, E.\n                and \n                  Witten, I.H.\n                (2009), \u201cHuman-competitive tagging using automatic key phrase extraction\u201d, EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing Singapore, Vol. 3, pp. 1318-1327.","DOI":"10.3115\/1699648.1699678"},{"key":"key2022012720162424900_b13","doi-asserted-by":"crossref","unstructured":"Mostashari, A.\n         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