LEADER 01715oam 2200481I 450 001 9910704008903321 005 20160128155915.0 035 $a(CKB)5470000002437570 035 $a(OCoLC)846865949 035 $a(OCoLC)995470000002437570 035 $a(EXLCZ)995470000002437570 100 $a20130605d2012 ua 0 101 0 $aeng 135 $aurbn||||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aDo retail mergers affect competition? $eevidence from grocery retailing /$fDaniel Hosken, Luke M. Olson, Loren K. Smith 210 1$aWashington, DC :$cBureau of Economics, Federal Trade Commission,$d2012. 215 $a1 online resource (45 unnumbered pages) $cillustrations 225 1 $aWorking paper ;$vno. 313 300 $aTitle from PDF title page (viewed on June 5, 2013). 300 $a"December 2012." 320 $aIncludes bibliographical references (pages 31-34). 517 $aDo retail mergers affect competition? 606 $aGrocery trade$xMergers$zUnited States 606 $aConsolidation and merger of corporations$xEconomic aspects$zUnited States 606 $aCompetition$zUnited States 615 0$aGrocery trade$xMergers 615 0$aConsolidation and merger of corporations$xEconomic aspects 615 0$aCompetition 700 $aHosken$b Daniel$01381181 702 $aOlson$b Luke M. 702 $aSmith$b Loren K. 712 02$aUnited States.$bFederal Trade Commission.$bBureau of Economics, 801 0$bAZS 801 1$bAZS 801 2$bOCLCQ 801 2$bGPO 906 $aBOOK 912 $a9910704008903321 996 $aDo retail mergers affect competition$93450601 997 $aUNINA LEADER 04836nam 22007935 450 001 9910298973603321 005 20251117080051.0 010 $a3-319-10377-6 024 7 $a10.1007/978-3-319-10377-8 035 $a(CKB)3710000000277584 035 $a(EBL)1965455 035 $a(SSID)ssj0001386071 035 $a(PQKBManifestationID)11752455 035 $a(PQKBTitleCode)TC0001386071 035 $a(PQKBWorkID)11350160 035 $a(PQKB)10811299 035 $a(MiAaPQ)EBC1965455 035 $a(DE-He213)978-3-319-10377-8 035 $a(PPN)183088727 035 $a(EXLCZ)993710000000277584 100 $a20141106d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMeasuring Scholarly Impact $eMethods and Practice /$fedited by Ying Ding, Ronald Rousseau, Dietmar Wolfram 205 $a1st ed. 2014. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014. 215 $a1 online resource (351 p.) 300 $aDescription based upon print version of record. 311 08$a3-319-10376-8 320 $aIncludes bibliographical references and index. 327 $aCommunity detection and visualization of networks with the map equation framework -- Link Prediction -- Network analysis and indicators -- PageRank-related methods for analyzing citation networks -- Systems Life Cycle and its relation with the Triple Helix -- Spatial scientometrics and scholarly impact: A review of recent studies, tools and methods -- Researchers? publication patterns and their use for author disambiguation -- Knowledge integration and diffusion: Measures and mapping of diversity and coherence -- Limited dependent variables models and probabilistic prediction in informetrics -- Text mining with the Stanford CoreNLP -- Topic modeling: Measuring scholarly impact using a topical lens -- The substantive and practical significance of citation impact differences between institutions: Guidelines for the analysis of percentiles using effect sizes and confidence intervals -- Visualizing bibliometric networks -- Replicable science of science studies. 330 $aThis book is an authoritative handbook of current topics, technologies and methodological approaches that may be used for the study of scholarly impact. The included methods cover a range of fields such as statistical sciences, scientific visualization, network analysis, text mining, and information retrieval. The techniques and tools enable researchers to investigate metric phenomena and to assess scholarly impact in new ways. Each chapter offers an introduction to the selected topic and outlines how the topic, technology or methodological approach may be applied to metrics-related research. Comprehensive and up-to-date, Measuring Scholarly Impact: Methods and Practice is designed for researchers and scholars interested in informetrics, scientometrics, and text mining. The hands-on perspective is also beneficial to advanced-level students in fields from computer science and statistics to information science. 606 $aInformation storage and retrieval 606 $aStatistics 606 $aData mining 606 $aArtificial intelligence 606 $aMathematics 606 $aVisualization 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 606 $aStatistics for Social Sciences, Humanities, Law$3https://scigraph.springernature.com/ontologies/product-market-codes/S17040 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aVisualization$3https://scigraph.springernature.com/ontologies/product-market-codes/M14034 615 0$aInformation storage and retrieval. 615 0$aStatistics. 615 0$aData mining. 615 0$aArtificial intelligence. 615 0$aMathematics. 615 0$aVisualization. 615 14$aInformation Storage and Retrieval. 615 24$aStatistics for Social Sciences, Humanities, Law. 615 24$aData Mining and Knowledge Discovery. 615 24$aArtificial Intelligence. 615 24$aVisualization. 676 $a004 676 $a006 676 $a006.312 676 $a025.04 676 $a519.5 702 $aDing$b Ying$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRousseau$b R.$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aWolfram$b Dietmar$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910298973603321 996 $aMeasuring Scholarly Impact$91953990 997 $aUNINA