Information and Knowledge Management using ArcGIS ModelBuilder

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Paulo João, Jorge Ferreira and José Martins Analyzing crime data by the actual divisions and by the new ones, it seems obvious an increase in numbers (in part due to the aggregation of values recorded in several parishes that lead to new administrative area). Significantly, the low number of crimes in the small villages of the current division changed from the first to the last value class (when aggregated the new administrative division). The data shows a very large criminal density on Oriente, but the empirical knowledge of this area can tell us that most criminal incidents occur in its (old) aggregated neighborhood. Next, the calculation of criminal density for the parish was made, dividing the total crimes per square Km in area. Figure 5: Ratio of total crimes per square Km in Lisbon Regarding criminal density, the new administrative division gives the perception of a decrease in crime numbers. However, this fact is in part related to the significant increase in the area of some parishes, thus reducing the density of crimes. In order to understand how it would be the spatial representation of crime according to the city's population, it was created a criminal incidence rate, dividing the number of crimes by the population; the results were expressed in ‰. The data used for the calculation was from 2001, the Population Census conducted by the National Statistics Institute (INE). It would be appropriate to use more recent values (for example the population in 2009) but it was not possible due to the fact that the census is made every 10 years. When it comes to an evaluation of numbers, for example criminal incidence rates, the new administrative division gives the perception of a decline. The reduction is in part due to the significant increase in the area of some parishes and their residents, thus reducing the incidence rate of crime in certain districts of the new administrative division. It is a well know fact that the southern part of the city, corresponding to the downtown district, correspond to an area that has the highest number of crimes, mainly because it is the center of major economic, financial and commercial activities. But also because it’s the main tourism “spot” in the city, which triggers criminal activity. In order to achieve different perspectives when analyzing the crime results across the city, it was decided to make the sum of the resident population with the mobility of population (population that enter and circulate in the city like daily workers and tourists), in the sense that only by analyzing the 220
Paulo João, Jorge Ferreira and José Martins criminal statistics according to the resident population of Lisbon, may be to overemphasize the intensity of occurrence. Assuming that a large number of resident population plus the other group may lead to higher crime rates. (Machado, et. al. 2007:138). Figure 6: Ratio of criminal incidence per 1000 inhabitants in Lisbon Figure 7: Ratio of criminal incidence per 1000 inhabitants and presents in Lisbon 221
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Proceedings of the 5th European Con
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Contents Paper Title Author(s) Page
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Paper Title Author(s) Page No. Cont
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Preface The 5th European Conference
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Dr Jorge Ricardo da Costa Ferreira
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LSE while working at the British St
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Minna Isomursu, PhD, is a research
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Elmarie Papageorgiou is a Senior Le
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Information and Knowledge Managemen
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João Agrela et al. So modeling bec
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João Agrela et al. ETRS 89 project
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João Agrela et al. (accidents) tha
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Figure 8: Final model João Agrela
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João Agrela et al. outputs and res
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System Integration Model Based on O
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Kamsuriah Ahmad, Azwan Mohamed and
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Kamsuriah Ahmad, Azwan Mohamed and
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Building Virtual Communities on top
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Cuneyt Gurcan Akcora, Barbara Carmi
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References Cuneyt Gurcan Akcora, Ba
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Karen Anderson, Göran Samuelsson a
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Developing a Model for Assessing IT
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Mohammad Abooyee Ardakan et al. Fig
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Mohammad Abooyee Ardakan et al. cor
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Investigating the Relationship of M
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Mohammad Abooyee Ardakan, Babak Soh
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Table 3: Goodness of fit indices Mo
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Evaluation of ICT Investment in Hea
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Figure 1: Search strategy for syste
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A. Arviansyah, Egon Berghout and Ch
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Managerial A. Arviansyah, Egon Berg
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The Uses of Business Outcomes for I
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Dawit Asmelash Measurability of th
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Dawit Asmelash affected business pr
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Business Units HR Sales Step 2 Iden
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Dawit Asmelash In this case, at thi
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Data Governance in Practice: The SM
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Carolyn Begg and Tom Caira Our rese
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Carolyn Begg and Tom Caira In the f
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Carolyn Begg and Tom Caira Decision
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Carolyn Begg and Tom Caira SMEs nee
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Fergal Carton et al. The language u
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Fergal Carton et al. 2008) to abstr
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Payment integration (payment produc
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Fergal Carton et al. Kim,C., Mirsob
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Walter Castelnovo devised for, have
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Walter Castelnovo the potential ris
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Walter Castelnovo allow the informa
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Walter Castelnovo Risk assessment,
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Embedding Human Values Into Informa
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Sunil Choenni, Peter van Waart and
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Evaluating the Role and Potential o
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Renata Paola Dameri For these reaso
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Final assessment and evaluation. Re
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Renata Paola Dameri STRATEGIC GOALS
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Renata Paola Dameri To clearly com
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ICT and PA: A Marriage Made in Heav
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Maria Concetta De Vivo, Alberto Pol
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Jan Devos, Hendrik Van Landeghem an
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References Jan Devos, Hendrik Van L
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Luciana Duranti and Adam Jansen Dig
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Luciana Duranti and Adam Jansen A
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References Luciana Duranti and Adam
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Kate Dymoke-Bradshaw and Ann Brown
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Graham Fletcher and Marie Cahillane
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How Open Source Software Products:
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Chiara Friso, Valentina Lenarduzzi,
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Il giornale elettronico (Trivella,
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Yuwanuch Gulatee and Barbara Combes
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Page 187 and 188: Yuwanuch Gulatee and Barbara Combes
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Page 191 and 192: Florian Hamel, Thomas Ph. Herz, Fal
Page 199 and 200: Martin Hill, John Salt and Graham F
Page 205 and 206: Transforming Information to Knowled
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Page 215 and 216: 3. Theoretical discussion 3.1 Green
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Page 225 and 226: 4.2 Challenges with research method
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Page 229 and 230: The Geography of Criminality - Info
Page 231 and 232: Intelligence Paulo João, Jorge Fer
Page 233 and 234: 4.1 Crime hot-spots Paulo João, Jo
Page 235: Paulo João, Jorge Ferreira and Jos
Page 239 and 240: Paulo João, Jorge Ferreira and Jos
Page 241 and 242: Mobile Virtual Network Operator Inf
Page 243 and 244: Hallur Leivsgarð Joensen and Torbe
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Page 259 and 260: A Fair Partnership Model by Sharing
Page 261 and 262: Ghassan Kbar 2. Partnership and VC
Page 263 and 264: Ghassan Kbar Entering state of the
Page 265 and 266: Ghassan Kbar Saudi-chamber, (2011)
Page 267 and 268: Ghassan Kbar and Abdul Aziz AlDusar
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Portfolio Management in Non-Profit
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Bert Kleersnijder and Egon Berghout
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Why is an IS Project Late? - A Case
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2. The project 2.1 Background and r
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Juha Kontio Phase In stallation Ope
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Table 2: Identified reason of the p
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Juha Kontio There are also reasons
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2. Performance review model for NDP
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Misoo Kwon Among the review indicat
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Type Average time saved Misoo Kwon
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Luigi Lavazza In conclusion, when a
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Luigi Lavazza The former can be de
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Luigi Lavazza For each process, we
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6. Conclusions Luigi Lavazza When e
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eBusiness Model Design and Evaluati
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Monika Magnusson categories of busi
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Monika Magnusson Business Model Ele
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5.2 Guiding questions Monika Magnus
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Monika Magnusson Hay, M. and Kamsha
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Monika Magnusson and Marie-Therese
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4.3 Goals at the project level Moni
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Alignment in Enterprise Architectur
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Thanos Magoulas, Aida Hadzic, Ted S
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3.4 Infological alignment Thanos Ma
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Panagiotis Manolitzas et al. to Gov
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Panagiotis Manolitzas et al. Anothe
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Table 1: Criteria weights and satis
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Panagiotis Manolitzas et al. Satisf
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Understanding the Impact of Knowled
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Magdeline Mashilo and Tiko Iyamu Ac
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Magdeline Mashilo and Tiko Iyamu Cu
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Magdeline Mashilo and Tiko Iyamu Th
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Magdeline Mashilo and Tiko Iyamu Ho
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2. Literature review 2.1 The Batik
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Nor Laila Md Noor and Ariza Nordin
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Nor Laila Md Noor and Ariza Nordin
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Isolated Strategies Nor Laila Md No
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HOT-fit Evaluation Framework: Valid
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Maryati Mohd Yusof In order to vali
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Maryati Mohd Yusof Further framewor
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Maryati Mohd Yusof Kaplan, B., and
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Gunilla Myreteg social context (Orl
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Gunilla Myreteg needed routine. Ano
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Gunilla Myreteg used, which in turn
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Environmental Scanning Practice of
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Roslina Othman and Siti Rohimi Hame
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5. Conclusion Roslina Othman and Si
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Understanding Financial and non-Fin
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Elmarie Papageorgiou and Herman de
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Type of non-financial information a
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Shabnam Pasandide, Abbas Toloie Esh
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Can eGovernment Systems Bridge the
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Higher quality of services Elias Pi
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Elias Pimenidis, Lazaros Iliadis, a
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Elias Pimenidis, Lazaros Iliadis, a
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Contributions to the Measurement an
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Rui Alexandre Pires and Maria do C
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assessment Rui Alexandre Pires and
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Rozilawati Razali and Mahamsiatus K
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Figure 1: Research design 3.2 Phase
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David Sammon, Tadhg Nagle and John
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Teresa Santos, Ségio Freire and Jo
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Reflections on the Role of the Lect
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3. Reflective practice Elsje Scott,
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Elsje Scott, Peter Weimann and Nata
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Elena Serova traditional ERP manage
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Elena Serova Increase in percentag
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9. Conclusion Elena Serova At prese
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Sharina Tajul Urus, Alemayehu Molla
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4.2 Description of feral systems Sh
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Sharina Tajul Urus, Alemayehu Molla
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Type Sharina Tajul Urus, Alemayehu
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Open Source Disease Control Softwar
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Jose Teixeira and Reima Suomi do no
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Jose Teixeira and Reima Suomi from
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Jose Teixeira and Reima Suomi Futur
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Value of Knowledge Management Syste
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Nelly Todorova Human capital repres
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Nelly Todorova IT value from pure f
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Nelly Todorova unique and inimitabl
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Accountability and the Reconstructi
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Geert-Jan van Bussel cluding the pr
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Geert-Jan van Bussel (e.g., Wijnhov
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Geert-Jan van Bussel complementary,
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The Question of Selecting Appropria
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Bartosz Wachnik We can discern two
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Bartosz Wachnik Table 1: Criteria o
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Tasks in an ERP implementation proj
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Bartosz Wachnik Tests’ recapitul
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PhD Research Papers 501
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Information Systems for Production
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Denisa Ferenčíková 3. Correctly
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Denisa Ferenčíková method requir
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Denisa Ferenčíková mentioned typ
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1.2 Service oriented architecture A
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Antonio Hidalgo Landa, Ian Owens an
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Hesbon Nyagowa, Dennis Ocholla and
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The Specification of Competency Que
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Yadary Ortega-González et al. Figu
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Yadary Ortega-González et al. merg
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Yadary Ortega-González et al. Comp
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Yadary Ortega-González et al. Lysa
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Michal Pivnička to (Collis 2008),
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Figure 2: List of scorecards window
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Michal Pivnička A Custom view (fig
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Michal Pivnička necessary calculat
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Michal Pivnička combines two or mo
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Michal Pivnička When any informati
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Challenges in Business Case Develop
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Bart-Jan van Putten, Franziska Brec
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Bart-Jan van Putten and Markus Schi
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Mohamad Norzamani Sahroni and Marya
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Table 1: Type of medical error Moha
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Mohamad Norzamani Sahroni and Marya
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Non Academic Papers 577
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Management of Waiting List for Surg
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Rita Cristóvão and Pedro Gomes In
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Figure 4: Circuit of the patient in
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Rita Cristóvão and Pedro Gomes Fi
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Rita Cristóvão and Pedro Gomes ne
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Rita Cristóvão and Pedro Gomes Fi
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Rita Cristóvão and Pedro Gomes T
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Work in Progress Papers with Poster
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Information Management Enabling Col
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Maria Bergenstjerna Data will be co
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2. Methodology Giovanni Camponovo R
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Giovanni Camponovo separate concept
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Giovanni Camponovo A graphical summ
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Giovanni Camponovo 3.5 Motivations
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Giovanni Camponovo Butler, B., Spro
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An Enterprise Ontology Approach for
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Bernardo Gomes, André Vasconcelos
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Soudabeh Khodambashi and Maryati Mo
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National ICT Strategy and its Imple
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Ermelinda Kordha and As. Kozeta Sev
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João Soares, José Tribolet and An
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João Soares, José Tribolet and An
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