The Impacts of Entrepreneurship on Wealth Distribution View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-12

AUTHORS

Yi Zhu, Aziz Guergachi, Huaxiong Huang

ABSTRACT

Using mathematical statistical mechanics methods, this paper shows that decisions to heavily promote entrepreneurship beyond a certain threshold in a society would lead to an increase in the society’s Gini coefficient, and thus to more economic inequalities. More specifically, we show that, in a heterogeneous society made up of both entrepreneurs (Es) and ordinary agents (OAs), economic inequalities reach a minimum at an optimal ratio of ‘Es to OAs’. When dealing with a purely homogeneous society made up of entrepreneurs only or ordinary agents only, economic inequalities would decrease as trading activities intensify among the society’s agents. In particular, ideologies that consist in flattening the wealth/income of citizens (as it was recommended, for example, by communist regimes in the last century) to reduce economic inequalities through strict government interventions, may not lead to positive outcomes. We also show that introducing a little heterogeneity into a purely homogeneous society will help reduce economic inequalities in this society. Thus, a society that is composed of ordinary agents only will see its economic inequalities decrease if a number of entrepreneurs join this society. Vice-versa, a society of entrepreneurs only will have its inequalities reduced if some ordinary agents join this society and engage the pre-existing entrepreneurs in trading activities; one could think of southern San Francisco Bay Area, Silicon Valley, as a concrete example of such a situation. To encourage ordinary agents become entrepreneurs, governments could design and implement tax-incentive policies for their respective societies. While such tax-incentive policies would help increase the number of entrepreneurs in the targeted society, they would also have unintended consequences: the society’s middle class gets depleted at equilibrium, and the inequalities that result from implementing the aforementioned policies will be uniformly bigger than the ones that result from an equal tax redistribution policy. The paper concludes with a discussion section that raises a number of questions about socio-economic phenomena and explains how these phenomena can be accounted for using physics laws and principles. More... »

PAGES

1-21

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10955-018-2160-4

DOI

http://dx.doi.org/10.1007/s10955-018-2160-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107529881


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/2008/1402", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Applied Economics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/14", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Economics", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "York University", 
          "id": "https://www.grid.ac/institutes/grid.21100.32", 
          "name": [
            "Department of Mathematics and Statistics, York University, Toronto, ON, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhu", 
        "givenName": "Yi", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Ryerson University", 
          "id": "https://www.grid.ac/institutes/grid.68312.3e", 
          "name": [
            "Department of Mathematics and Statistics, York University, Toronto, ON, Canada", 
            "Ted Rogers School of Management, Information Technology Management, Ryerson University, Toronto, ON, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Guergachi", 
        "givenName": "Aziz", 
        "id": "sg:person.01103751703.37", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01103751703.37"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Fields Institute for Research in Mathematical Sciences", 
          "id": "https://www.grid.ac/institutes/grid.249304.8", 
          "name": [
            "Department of Mathematics and Statistics, York University, Toronto, ON, Canada", 
            "The Fields Institute, Toronto, ON, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Huang", 
        "givenName": "Huaxiong", 
        "id": "sg:person.01063335042.95", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01063335042.95"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s10955-007-9462-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001076273", 
          "https://doi.org/10.1007/s10955-007-9462-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10955-012-0653-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003862771", 
          "https://doi.org/10.1007/s10955-012-0653-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/4-431-28915-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004168747", 
          "https://doi.org/10.1007/4-431-28915-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/4-431-28915-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004168747", 
          "https://doi.org/10.1007/4-431-28915-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0378-4371(00)00205-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005035505"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.69.046102", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013693430"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.69.046102", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013693430"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physa.2007.05.062", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015892774"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00332-013-9185-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016366268", 
          "https://doi.org/10.1007/s00332-013-9185-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.66.031102", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026094390"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.66.031102", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026094390"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1098/rsta.2013.0394", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026532957"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1057/9780230295155", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030953670", 
          "https://doi.org/10.1057/9780230295155"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1057/9780230295155", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030953670", 
          "https://doi.org/10.1057/9780230295155"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physa.2005.04.038", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042944236"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physa.2005.04.038", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042944236"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2276207", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045544084"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physa.2011.08.013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046050203"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10955-013-0888-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053679094", 
          "https://doi.org/10.1007/s10955-013-0888-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4310/cms.2008.v6.n4.a12", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1072458880"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/cbo9781139004169", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098662969"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3917/droz.paret.1964.01", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1099332634"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-12", 
    "datePublishedReg": "2018-12-01", 
    "description": "Using mathematical statistical mechanics methods, this paper shows that decisions to heavily promote entrepreneurship beyond a certain threshold in a society would lead to an increase in the society\u2019s Gini coefficient, and thus to more economic inequalities. More specifically, we show that, in a heterogeneous society made up of both entrepreneurs (Es) and ordinary agents (OAs), economic inequalities reach a minimum at an optimal ratio of \u2018Es to OAs\u2019. When dealing with a purely homogeneous society made up of entrepreneurs only or ordinary agents only, economic inequalities would decrease as trading activities intensify among the society\u2019s agents. In particular, ideologies that consist in flattening the wealth/income of citizens (as it was recommended, for example, by communist regimes in the last century) to reduce economic inequalities through strict government interventions, may not lead to positive outcomes. We also show that introducing a little heterogeneity into a purely homogeneous society will help reduce economic inequalities in this society. Thus, a society that is composed of ordinary agents only will see its economic inequalities decrease if a number of entrepreneurs join this society. Vice-versa, a society of entrepreneurs only will have its inequalities reduced if some ordinary agents join this society and engage the pre-existing entrepreneurs in trading activities; one could think of southern San Francisco Bay Area, Silicon Valley, as a concrete example of such a situation. To encourage ordinary agents become entrepreneurs, governments could design and implement tax-incentive policies for their respective societies. While such tax-incentive policies would help increase the number of entrepreneurs in the targeted society, they would also have unintended consequences: the society\u2019s middle class gets depleted at equilibrium, and the inequalities that result from implementing the aforementioned policies will be uniformly bigger than the ones that result from an equal tax redistribution policy. The paper concludes with a discussion section that raises a number of questions about socio-economic phenomena and explains how these phenomena can be accounted for using physics laws and principles.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10955-018-2160-4", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1040979", 
        "issn": [
          "0022-4715", 
          "1572-9613"
        ], 
        "name": "Journal of Statistical Physics", 
        "type": "Periodical"
      }
    ], 
    "name": "The Impacts of Entrepreneurship on Wealth Distribution", 
    "pagination": "1-21", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "38b7e90eb6b260dc9f985ca53882ae8dddcc040b3732a63f59e388655511ac70"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10955-018-2160-4"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1107529881"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10955-018-2160-4", 
      "https://app.dimensions.ai/details/publication/pub.1107529881"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T00:24", 
    "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/v90/0000000001_0000000264/records_8695_00000559.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs10955-018-2160-4"
  }
]
 

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/s10955-018-2160-4'

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/s10955-018-2160-4'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10955-018-2160-4'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10955-018-2160-4'


 

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

133 TRIPLES      21 PREDICATES      42 URIs      17 LITERALS      5 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10955-018-2160-4 schema:about anzsrc-for:14
2 anzsrc-for:1402
3 schema:author Ndfa81dec9e604c219238188e5f63ff61
4 schema:citation sg:pub.10.1007/4-431-28915-1
5 sg:pub.10.1007/s00332-013-9185-2
6 sg:pub.10.1007/s10955-007-9462-2
7 sg:pub.10.1007/s10955-012-0653-0
8 sg:pub.10.1007/s10955-013-0888-4
9 sg:pub.10.1057/9780230295155
10 https://doi.org/10.1016/j.physa.2005.04.038
11 https://doi.org/10.1016/j.physa.2007.05.062
12 https://doi.org/10.1016/j.physa.2011.08.013
13 https://doi.org/10.1016/s0378-4371(00)00205-3
14 https://doi.org/10.1017/cbo9781139004169
15 https://doi.org/10.1098/rsta.2013.0394
16 https://doi.org/10.1103/physreve.66.031102
17 https://doi.org/10.1103/physreve.69.046102
18 https://doi.org/10.2307/2276207
19 https://doi.org/10.3917/droz.paret.1964.01
20 https://doi.org/10.4310/cms.2008.v6.n4.a12
21 schema:datePublished 2018-12
22 schema:datePublishedReg 2018-12-01
23 schema:description Using mathematical statistical mechanics methods, this paper shows that decisions to heavily promote entrepreneurship beyond a certain threshold in a society would lead to an increase in the society’s Gini coefficient, and thus to more economic inequalities. More specifically, we show that, in a heterogeneous society made up of both entrepreneurs (Es) and ordinary agents (OAs), economic inequalities reach a minimum at an optimal ratio of ‘Es to OAs’. When dealing with a purely homogeneous society made up of entrepreneurs only or ordinary agents only, economic inequalities would decrease as trading activities intensify among the society’s agents. In particular, ideologies that consist in flattening the wealth/income of citizens (as it was recommended, for example, by communist regimes in the last century) to reduce economic inequalities through strict government interventions, may not lead to positive outcomes. We also show that introducing a little heterogeneity into a purely homogeneous society will help reduce economic inequalities in this society. Thus, a society that is composed of ordinary agents only will see its economic inequalities decrease if a number of entrepreneurs join this society. Vice-versa, a society of entrepreneurs only will have its inequalities reduced if some ordinary agents join this society and engage the pre-existing entrepreneurs in trading activities; one could think of southern San Francisco Bay Area, Silicon Valley, as a concrete example of such a situation. To encourage ordinary agents become entrepreneurs, governments could design and implement tax-incentive policies for their respective societies. While such tax-incentive policies would help increase the number of entrepreneurs in the targeted society, they would also have unintended consequences: the society’s middle class gets depleted at equilibrium, and the inequalities that result from implementing the aforementioned policies will be uniformly bigger than the ones that result from an equal tax redistribution policy. The paper concludes with a discussion section that raises a number of questions about socio-economic phenomena and explains how these phenomena can be accounted for using physics laws and principles.
24 schema:genre research_article
25 schema:inLanguage en
26 schema:isAccessibleForFree false
27 schema:isPartOf sg:journal.1040979
28 schema:name The Impacts of Entrepreneurship on Wealth Distribution
29 schema:pagination 1-21
30 schema:productId N01051cec3d9b4c5fa88f3945c12c8784
31 N7a8a81cbbe7a4cb287f70fd5685cf275
32 Nc3656fba6c364d93b66c4ec576aedb06
33 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107529881
34 https://doi.org/10.1007/s10955-018-2160-4
35 schema:sdDatePublished 2019-04-11T00:24
36 schema:sdLicense https://scigraph.springernature.com/explorer/license/
37 schema:sdPublisher Nb93a7e01b5044a36962700eed4bbe954
38 schema:url https://link.springer.com/10.1007%2Fs10955-018-2160-4
39 sgo:license sg:explorer/license/
40 sgo:sdDataset articles
41 rdf:type schema:ScholarlyArticle
42 N01051cec3d9b4c5fa88f3945c12c8784 schema:name readcube_id
43 schema:value 38b7e90eb6b260dc9f985ca53882ae8dddcc040b3732a63f59e388655511ac70
44 rdf:type schema:PropertyValue
45 N4edf7fb23da84c9a8c6aa4b62b4ad488 rdf:first sg:person.01063335042.95
46 rdf:rest rdf:nil
47 N7a8a81cbbe7a4cb287f70fd5685cf275 schema:name doi
48 schema:value 10.1007/s10955-018-2160-4
49 rdf:type schema:PropertyValue
50 N7b07156b105c4246ab4bb3e054a20fde schema:affiliation https://www.grid.ac/institutes/grid.21100.32
51 schema:familyName Zhu
52 schema:givenName Yi
53 rdf:type schema:Person
54 N807e95fe470d48c2a4e29a129685b11c rdf:first sg:person.01103751703.37
55 rdf:rest N4edf7fb23da84c9a8c6aa4b62b4ad488
56 Nb93a7e01b5044a36962700eed4bbe954 schema:name Springer Nature - SN SciGraph project
57 rdf:type schema:Organization
58 Nc3656fba6c364d93b66c4ec576aedb06 schema:name dimensions_id
59 schema:value pub.1107529881
60 rdf:type schema:PropertyValue
61 Ndfa81dec9e604c219238188e5f63ff61 rdf:first N7b07156b105c4246ab4bb3e054a20fde
62 rdf:rest N807e95fe470d48c2a4e29a129685b11c
63 anzsrc-for:14 schema:inDefinedTermSet anzsrc-for:
64 schema:name Economics
65 rdf:type schema:DefinedTerm
66 anzsrc-for:1402 schema:inDefinedTermSet anzsrc-for:
67 schema:name Applied Economics
68 rdf:type schema:DefinedTerm
69 sg:journal.1040979 schema:issn 0022-4715
70 1572-9613
71 schema:name Journal of Statistical Physics
72 rdf:type schema:Periodical
73 sg:person.01063335042.95 schema:affiliation https://www.grid.ac/institutes/grid.249304.8
74 schema:familyName Huang
75 schema:givenName Huaxiong
76 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01063335042.95
77 rdf:type schema:Person
78 sg:person.01103751703.37 schema:affiliation https://www.grid.ac/institutes/grid.68312.3e
79 schema:familyName Guergachi
80 schema:givenName Aziz
81 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01103751703.37
82 rdf:type schema:Person
83 sg:pub.10.1007/4-431-28915-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004168747
84 https://doi.org/10.1007/4-431-28915-1
85 rdf:type schema:CreativeWork
86 sg:pub.10.1007/s00332-013-9185-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016366268
87 https://doi.org/10.1007/s00332-013-9185-2
88 rdf:type schema:CreativeWork
89 sg:pub.10.1007/s10955-007-9462-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001076273
90 https://doi.org/10.1007/s10955-007-9462-2
91 rdf:type schema:CreativeWork
92 sg:pub.10.1007/s10955-012-0653-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003862771
93 https://doi.org/10.1007/s10955-012-0653-0
94 rdf:type schema:CreativeWork
95 sg:pub.10.1007/s10955-013-0888-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053679094
96 https://doi.org/10.1007/s10955-013-0888-4
97 rdf:type schema:CreativeWork
98 sg:pub.10.1057/9780230295155 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030953670
99 https://doi.org/10.1057/9780230295155
100 rdf:type schema:CreativeWork
101 https://doi.org/10.1016/j.physa.2005.04.038 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042944236
102 rdf:type schema:CreativeWork
103 https://doi.org/10.1016/j.physa.2007.05.062 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015892774
104 rdf:type schema:CreativeWork
105 https://doi.org/10.1016/j.physa.2011.08.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046050203
106 rdf:type schema:CreativeWork
107 https://doi.org/10.1016/s0378-4371(00)00205-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005035505
108 rdf:type schema:CreativeWork
109 https://doi.org/10.1017/cbo9781139004169 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098662969
110 rdf:type schema:CreativeWork
111 https://doi.org/10.1098/rsta.2013.0394 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026532957
112 rdf:type schema:CreativeWork
113 https://doi.org/10.1103/physreve.66.031102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026094390
114 rdf:type schema:CreativeWork
115 https://doi.org/10.1103/physreve.69.046102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013693430
116 rdf:type schema:CreativeWork
117 https://doi.org/10.2307/2276207 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045544084
118 rdf:type schema:CreativeWork
119 https://doi.org/10.3917/droz.paret.1964.01 schema:sameAs https://app.dimensions.ai/details/publication/pub.1099332634
120 rdf:type schema:CreativeWork
121 https://doi.org/10.4310/cms.2008.v6.n4.a12 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072458880
122 rdf:type schema:CreativeWork
123 https://www.grid.ac/institutes/grid.21100.32 schema:alternateName York University
124 schema:name Department of Mathematics and Statistics, York University, Toronto, ON, Canada
125 rdf:type schema:Organization
126 https://www.grid.ac/institutes/grid.249304.8 schema:alternateName Fields Institute for Research in Mathematical Sciences
127 schema:name Department of Mathematics and Statistics, York University, Toronto, ON, Canada
128 The Fields Institute, Toronto, ON, Canada
129 rdf:type schema:Organization
130 https://www.grid.ac/institutes/grid.68312.3e schema:alternateName Ryerson University
131 schema:name Department of Mathematics and Statistics, York University, Toronto, ON, Canada
132 Ted Rogers School of Management, Information Technology Management, Ryerson University, Toronto, ON, Canada
133 rdf:type schema:Organization
 




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


...