Network externalities in online video games: an empirical analysis utilizing online product ratings View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2015-12

AUTHORS

Yong Liu, Enping Shirley Mai, Jun Yang

ABSTRACT

Video games have become a major contributor to the USA and global economy. This paper studies network externalities in the online video game industry. Even though network externalities are recognized as a major driver of new product diffusion, testing the existence and the impact of network externalities at the individual level has been a challenge. By employing online product ratings in the estimation, we find that for online video games: (1) a larger installed base generates higher product ratings by individuals; (2) network externalities exhibit nonlinear dynamics over product life cycle—nonsignificant initially, highly significant next, and less significant in the later period; and (3) network externalities differ across consumer segments: the impact of the installed base is stronger on less-experienced consumers than on more-experienced ones. Our results suggest that network externalities should be treated as a dynamic rather than a time-invariant phenomenon and heterogeneous rather than homogeneous across consumers. More... »

PAGES

679-690

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11002-015-9390-x

DOI

http://dx.doi.org/10.1007/s11002-015-9390-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1020287483


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Arizona", 
          "id": "https://www.grid.ac/institutes/grid.134563.6", 
          "name": [
            "Department of Marketing, Eller College of Management, The University of Arizona, 85721, Tucson, AZ, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liu", 
        "givenName": "Yong", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "East Carolina University", 
          "id": "https://www.grid.ac/institutes/grid.255364.3", 
          "name": [
            "Department of Marketing and Supply Chain Management, East Carolina University, 27858, Greenville, NC, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mai", 
        "givenName": "Enping Shirley", 
        "id": "sg:person.016414650225.61", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016414650225.61"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Houston Victoria", 
          "id": "https://www.grid.ac/institutes/grid.462948.5", 
          "name": [
            "Discipline of Marketing, School of Business Administration, The University of Houston Victoria, 14000 University Blvd, 77479, Sugar Land, TX, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yang", 
        "givenName": "Jun", 
        "id": "sg:person.015760613635.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015760613635.46"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1509/jmkg.74.2.133", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003528343"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1509/jmkg.70.3.74", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014123946"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1509/jmkr.46.2.135", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015363039"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1509/jmkr.46.2.135", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015363039"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1509/jmkg.68.1.41.24026", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016073294"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1509/jmkg.68.1.41.24026", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016073294"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.omega.2006.03.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026686400"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1467-6451.2005.00268.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047886971"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1467-6451.2005.00268.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047886971"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/261409", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058574890"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/344399", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058640424"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/510229", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058787295"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1086/597049", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058804153"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/isre.1040.0020", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064711163"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/isre.11.1.61.11783", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064711415"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/mnsc.1060.0545", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064714574"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/mnsc.49.10.1407.17308", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064722293"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/1593691", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069559302"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2555859", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069991614"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11002-005-5902-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1086124195", 
          "https://doi.org/10.1007/s11002-005-5902-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11002-005-5902-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1086124195", 
          "https://doi.org/10.1007/s11002-005-5902-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11002-005-5902-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1086124195", 
          "https://doi.org/10.1007/s11002-005-5902-4"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2015-12", 
    "datePublishedReg": "2015-12-01", 
    "description": "Video games have become a major contributor to the USA and global economy. This paper studies network externalities in the online video game industry. Even though network externalities are recognized as a major driver of new product diffusion, testing the existence and the impact of network externalities at the individual level has been a challenge. By employing online product ratings in the estimation, we find that for online video games: (1) a larger installed base generates higher product ratings by individuals; (2) network externalities exhibit nonlinear dynamics over product life cycle\u2014nonsignificant initially, highly significant next, and less significant in the later period; and (3) network externalities differ across consumer segments: the impact of the installed base is stronger on less-experienced consumers than on more-experienced ones. Our results suggest that network externalities should be treated as a dynamic rather than a time-invariant phenomenon and heterogeneous rather than homogeneous across consumers.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s11002-015-9390-x", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1044599", 
        "issn": [
          "0923-0645", 
          "1573-059X"
        ], 
        "name": "Marketing Letters", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "4", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "26"
      }
    ], 
    "name": "Network externalities in online video games: an empirical analysis utilizing online product ratings", 
    "pagination": "679-690", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "60aa133a4a9720062a82458a6f693fadbbf1cbff5eb2996b1bf20ee1f06d7c76"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s11002-015-9390-x"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1020287483"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s11002-015-9390-x", 
      "https://app.dimensions.ai/details/publication/pub.1020287483"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T09:30", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000346_0000000346/records_99802_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs11002-015-9390-x"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s11002-015-9390-x'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s11002-015-9390-x'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11002-015-9390-x'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11002-015-9390-x'


 

This table displays all metadata directly associated to this object as RDF triples.

132 TRIPLES      21 PREDICATES      44 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s11002-015-9390-x schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author N1102b1381dee4ccfa37ce9b779521f7d
4 schema:citation sg:pub.10.1007/s11002-005-5902-4
5 https://doi.org/10.1016/j.omega.2006.03.008
6 https://doi.org/10.1086/261409
7 https://doi.org/10.1086/344399
8 https://doi.org/10.1086/510229
9 https://doi.org/10.1086/597049
10 https://doi.org/10.1111/j.1467-6451.2005.00268.x
11 https://doi.org/10.1287/isre.1040.0020
12 https://doi.org/10.1287/isre.11.1.61.11783
13 https://doi.org/10.1287/mnsc.1060.0545
14 https://doi.org/10.1287/mnsc.49.10.1407.17308
15 https://doi.org/10.1509/jmkg.68.1.41.24026
16 https://doi.org/10.1509/jmkg.70.3.74
17 https://doi.org/10.1509/jmkg.74.2.133
18 https://doi.org/10.1509/jmkr.46.2.135
19 https://doi.org/10.2307/1593691
20 https://doi.org/10.2307/2555859
21 schema:datePublished 2015-12
22 schema:datePublishedReg 2015-12-01
23 schema:description Video games have become a major contributor to the USA and global economy. This paper studies network externalities in the online video game industry. Even though network externalities are recognized as a major driver of new product diffusion, testing the existence and the impact of network externalities at the individual level has been a challenge. By employing online product ratings in the estimation, we find that for online video games: (1) a larger installed base generates higher product ratings by individuals; (2) network externalities exhibit nonlinear dynamics over product life cycle—nonsignificant initially, highly significant next, and less significant in the later period; and (3) network externalities differ across consumer segments: the impact of the installed base is stronger on less-experienced consumers than on more-experienced ones. Our results suggest that network externalities should be treated as a dynamic rather than a time-invariant phenomenon and heterogeneous rather than homogeneous across consumers.
24 schema:genre research_article
25 schema:inLanguage en
26 schema:isAccessibleForFree false
27 schema:isPartOf N20b22ad185c549f5b75b8ac3f4b48642
28 N9e40d626567e4f4fa28e1041d4465367
29 sg:journal.1044599
30 schema:name Network externalities in online video games: an empirical analysis utilizing online product ratings
31 schema:pagination 679-690
32 schema:productId N6ef564280b1049fabdd88c084898c4f2
33 N8f4bc06c7dea432aab1f9d3d9a1637a4
34 Nff142d4b757c4f2bad97577184f9e864
35 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020287483
36 https://doi.org/10.1007/s11002-015-9390-x
37 schema:sdDatePublished 2019-04-11T09:30
38 schema:sdLicense https://scigraph.springernature.com/explorer/license/
39 schema:sdPublisher Na039ba90da65472f84591dfd8edc40f0
40 schema:url https://link.springer.com/10.1007%2Fs11002-015-9390-x
41 sgo:license sg:explorer/license/
42 sgo:sdDataset articles
43 rdf:type schema:ScholarlyArticle
44 N1102b1381dee4ccfa37ce9b779521f7d rdf:first N31e738312dc542958e61670349e36121
45 rdf:rest N1e3b53ba9d31487c8e8baea430c4506c
46 N1e3b53ba9d31487c8e8baea430c4506c rdf:first sg:person.016414650225.61
47 rdf:rest N4f51ba4f2219448b936543e28ace30ba
48 N20b22ad185c549f5b75b8ac3f4b48642 schema:issueNumber 4
49 rdf:type schema:PublicationIssue
50 N31e738312dc542958e61670349e36121 schema:affiliation https://www.grid.ac/institutes/grid.134563.6
51 schema:familyName Liu
52 schema:givenName Yong
53 rdf:type schema:Person
54 N4f51ba4f2219448b936543e28ace30ba rdf:first sg:person.015760613635.46
55 rdf:rest rdf:nil
56 N6ef564280b1049fabdd88c084898c4f2 schema:name readcube_id
57 schema:value 60aa133a4a9720062a82458a6f693fadbbf1cbff5eb2996b1bf20ee1f06d7c76
58 rdf:type schema:PropertyValue
59 N8f4bc06c7dea432aab1f9d3d9a1637a4 schema:name dimensions_id
60 schema:value pub.1020287483
61 rdf:type schema:PropertyValue
62 N9e40d626567e4f4fa28e1041d4465367 schema:volumeNumber 26
63 rdf:type schema:PublicationVolume
64 Na039ba90da65472f84591dfd8edc40f0 schema:name Springer Nature - SN SciGraph project
65 rdf:type schema:Organization
66 Nff142d4b757c4f2bad97577184f9e864 schema:name doi
67 schema:value 10.1007/s11002-015-9390-x
68 rdf:type schema:PropertyValue
69 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
70 schema:name Information and Computing Sciences
71 rdf:type schema:DefinedTerm
72 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
73 schema:name Artificial Intelligence and Image Processing
74 rdf:type schema:DefinedTerm
75 sg:journal.1044599 schema:issn 0923-0645
76 1573-059X
77 schema:name Marketing Letters
78 rdf:type schema:Periodical
79 sg:person.015760613635.46 schema:affiliation https://www.grid.ac/institutes/grid.462948.5
80 schema:familyName Yang
81 schema:givenName Jun
82 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015760613635.46
83 rdf:type schema:Person
84 sg:person.016414650225.61 schema:affiliation https://www.grid.ac/institutes/grid.255364.3
85 schema:familyName Mai
86 schema:givenName Enping Shirley
87 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016414650225.61
88 rdf:type schema:Person
89 sg:pub.10.1007/s11002-005-5902-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1086124195
90 https://doi.org/10.1007/s11002-005-5902-4
91 rdf:type schema:CreativeWork
92 https://doi.org/10.1016/j.omega.2006.03.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026686400
93 rdf:type schema:CreativeWork
94 https://doi.org/10.1086/261409 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058574890
95 rdf:type schema:CreativeWork
96 https://doi.org/10.1086/344399 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058640424
97 rdf:type schema:CreativeWork
98 https://doi.org/10.1086/510229 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058787295
99 rdf:type schema:CreativeWork
100 https://doi.org/10.1086/597049 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058804153
101 rdf:type schema:CreativeWork
102 https://doi.org/10.1111/j.1467-6451.2005.00268.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1047886971
103 rdf:type schema:CreativeWork
104 https://doi.org/10.1287/isre.1040.0020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064711163
105 rdf:type schema:CreativeWork
106 https://doi.org/10.1287/isre.11.1.61.11783 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064711415
107 rdf:type schema:CreativeWork
108 https://doi.org/10.1287/mnsc.1060.0545 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064714574
109 rdf:type schema:CreativeWork
110 https://doi.org/10.1287/mnsc.49.10.1407.17308 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064722293
111 rdf:type schema:CreativeWork
112 https://doi.org/10.1509/jmkg.68.1.41.24026 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016073294
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1509/jmkg.70.3.74 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014123946
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1509/jmkg.74.2.133 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003528343
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1509/jmkr.46.2.135 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015363039
119 rdf:type schema:CreativeWork
120 https://doi.org/10.2307/1593691 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069559302
121 rdf:type schema:CreativeWork
122 https://doi.org/10.2307/2555859 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069991614
123 rdf:type schema:CreativeWork
124 https://www.grid.ac/institutes/grid.134563.6 schema:alternateName University of Arizona
125 schema:name Department of Marketing, Eller College of Management, The University of Arizona, 85721, Tucson, AZ, USA
126 rdf:type schema:Organization
127 https://www.grid.ac/institutes/grid.255364.3 schema:alternateName East Carolina University
128 schema:name Department of Marketing and Supply Chain Management, East Carolina University, 27858, Greenville, NC, USA
129 rdf:type schema:Organization
130 https://www.grid.ac/institutes/grid.462948.5 schema:alternateName University of Houston Victoria
131 schema:name Discipline of Marketing, School of Business Administration, The University of Houston Victoria, 14000 University Blvd, 77479, Sugar Land, TX, USA
132 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...