The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps
Geographic Information Systems (GIS) enable decision makers to view tabular data geographically, as maps. This simple yet powerful visual format appears to facilitate problem solving, yet how it does so is not clear, nor do we know the types of problems that benefit from this representation. To begi...
Ausführliche Beschreibung
Autor*in: |
Smelcer, John B. [verfasserIn] Carmel, Erran [verfasserIn] |
---|
Format: |
E-Artikel |
---|
Erschienen: |
Oxford, UK: Blackwell Publishing Ltd ; 1997 |
---|
Schlagwörter: |
---|
Umfang: |
Online-Ressource |
---|
Reproduktion: |
2007 ; Blackwell Publishing Journal Backfiles 1879-2005 |
---|---|
Übergeordnetes Werk: |
In: Decision sciences - Oxford : Wiley-Blackwell, 1988, 28(1997), 2, Seite 0 |
Übergeordnetes Werk: |
volume:28 ; year:1997 ; number:2 ; pages:0 |
Links: |
---|
DOI / URN: |
10.1111/j.1540-5915.1997.tb01316.x |
---|
Katalog-ID: |
NLEJ242482112 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | NLEJ242482112 | ||
003 | DE-627 | ||
005 | 20210707155736.0 | ||
007 | cr uuu---uuuuu | ||
008 | 120427s1997 xx |||||o 00| ||und c | ||
024 | 7 | |a 10.1111/j.1540-5915.1997.tb01316.x |2 doi | |
035 | |a (DE-627)NLEJ242482112 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
100 | 1 | |a Smelcer, John B. |e verfasserin |4 aut | |
245 | 1 | 0 | |a The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps |
264 | 1 | |a Oxford, UK |b Blackwell Publishing Ltd |c 1997 | |
300 | |a Online-Ressource | ||
336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
337 | |a nicht spezifiziert |b z |2 rdamedia | ||
338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
520 | |a Geographic Information Systems (GIS) enable decision makers to view tabular data geographically, as maps. This simple yet powerful visual format appears to facilitate problem solving, yet how it does so is not clear, nor do we know the types of problems that benefit from this representation. To begin to understand the contributions of geographic representations over tabular representations, we conducted a three-factor experiment in problem solving. The experiment contained two different representations (map and table), three different geographic relationships (proximity, adjacency, and containment), and three levels of task difficulty (low, medium, and high). We found that maps generally produced faster problem solving than tables, and that problem-solving time increased with task difficulty. Most importantly, for the proximity and adjacency geographic relationships we found that maps kept problem-solving time low, while tables tended to increase time dramatically. However, we found that the number of knowledge states for each task explains performance times quite well and is a useful tool for understanding performance differences and interaction effects. As tasks become more difficult, representing them as maps generally keeps the number of knowledge states small, while for tables, the number of knowledge states increases dramatically. Correspondingly, problem-solving times increase dramatically with tables, but not with maps.In sum, as difficulty increases, maps are more effective for problem-solving tasks. Using maps, the tasks are simplified using visual heuristics that keep problemsolving times and error rates from rising as quickly as they do with tables. | ||
533 | |d 2007 |f Blackwell Publishing Journal Backfiles 1879-2005 |7 |2007|||||||||| | ||
650 | 4 | |a Geographical Information System (GIS) | |
700 | 1 | |a Carmel, Erran |e verfasserin |4 aut | |
773 | 0 | 8 | |i In |t Decision sciences |d Oxford : Wiley-Blackwell, 1988 |g 28(1997), 2, Seite 0 |h Online-Ressource |w (DE-627)NLEJ243926456 |w (DE-600)2066218-X |x 1540-5915 |7 nnns |
773 | 1 | 8 | |g volume:28 |g year:1997 |g number:2 |g pages:0 |
856 | 4 | 0 | |u http://dx.doi.org/10.1111/j.1540-5915.1997.tb01316.x |q text/html |x Verlag |z Deutschlandweit zugänglich |3 Volltext |
912 | |a GBV_USEFLAG_U | ||
912 | |a ZDB-1-DJB | ||
912 | |a GBV_NL_ARTICLE | ||
951 | |a AR | ||
952 | |d 28 |j 1997 |e 2 |h 0 |
author_variant |
j b s jb jbs e c ec |
---|---|
matchkey_str |
article:15405915:1997----::hefcieesfifrnrpeettosomngrapolmov |
hierarchy_sort_str |
1997 |
publishDate |
1997 |
allfields |
10.1111/j.1540-5915.1997.tb01316.x doi (DE-627)NLEJ242482112 DE-627 ger DE-627 rakwb Smelcer, John B. verfasserin aut The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps Oxford, UK Blackwell Publishing Ltd 1997 Online-Ressource nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Geographic Information Systems (GIS) enable decision makers to view tabular data geographically, as maps. This simple yet powerful visual format appears to facilitate problem solving, yet how it does so is not clear, nor do we know the types of problems that benefit from this representation. To begin to understand the contributions of geographic representations over tabular representations, we conducted a three-factor experiment in problem solving. The experiment contained two different representations (map and table), three different geographic relationships (proximity, adjacency, and containment), and three levels of task difficulty (low, medium, and high). We found that maps generally produced faster problem solving than tables, and that problem-solving time increased with task difficulty. Most importantly, for the proximity and adjacency geographic relationships we found that maps kept problem-solving time low, while tables tended to increase time dramatically. However, we found that the number of knowledge states for each task explains performance times quite well and is a useful tool for understanding performance differences and interaction effects. As tasks become more difficult, representing them as maps generally keeps the number of knowledge states small, while for tables, the number of knowledge states increases dramatically. Correspondingly, problem-solving times increase dramatically with tables, but not with maps.In sum, as difficulty increases, maps are more effective for problem-solving tasks. Using maps, the tasks are simplified using visual heuristics that keep problemsolving times and error rates from rising as quickly as they do with tables. 2007 Blackwell Publishing Journal Backfiles 1879-2005 |2007|||||||||| Geographical Information System (GIS) Carmel, Erran verfasserin aut In Decision sciences Oxford : Wiley-Blackwell, 1988 28(1997), 2, Seite 0 Online-Ressource (DE-627)NLEJ243926456 (DE-600)2066218-X 1540-5915 nnns volume:28 year:1997 number:2 pages:0 http://dx.doi.org/10.1111/j.1540-5915.1997.tb01316.x text/html Verlag Deutschlandweit zugänglich Volltext GBV_USEFLAG_U ZDB-1-DJB GBV_NL_ARTICLE AR 28 1997 2 0 |
spelling |
10.1111/j.1540-5915.1997.tb01316.x doi (DE-627)NLEJ242482112 DE-627 ger DE-627 rakwb Smelcer, John B. verfasserin aut The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps Oxford, UK Blackwell Publishing Ltd 1997 Online-Ressource nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Geographic Information Systems (GIS) enable decision makers to view tabular data geographically, as maps. This simple yet powerful visual format appears to facilitate problem solving, yet how it does so is not clear, nor do we know the types of problems that benefit from this representation. To begin to understand the contributions of geographic representations over tabular representations, we conducted a three-factor experiment in problem solving. The experiment contained two different representations (map and table), three different geographic relationships (proximity, adjacency, and containment), and three levels of task difficulty (low, medium, and high). We found that maps generally produced faster problem solving than tables, and that problem-solving time increased with task difficulty. Most importantly, for the proximity and adjacency geographic relationships we found that maps kept problem-solving time low, while tables tended to increase time dramatically. However, we found that the number of knowledge states for each task explains performance times quite well and is a useful tool for understanding performance differences and interaction effects. As tasks become more difficult, representing them as maps generally keeps the number of knowledge states small, while for tables, the number of knowledge states increases dramatically. Correspondingly, problem-solving times increase dramatically with tables, but not with maps.In sum, as difficulty increases, maps are more effective for problem-solving tasks. Using maps, the tasks are simplified using visual heuristics that keep problemsolving times and error rates from rising as quickly as they do with tables. 2007 Blackwell Publishing Journal Backfiles 1879-2005 |2007|||||||||| Geographical Information System (GIS) Carmel, Erran verfasserin aut In Decision sciences Oxford : Wiley-Blackwell, 1988 28(1997), 2, Seite 0 Online-Ressource (DE-627)NLEJ243926456 (DE-600)2066218-X 1540-5915 nnns volume:28 year:1997 number:2 pages:0 http://dx.doi.org/10.1111/j.1540-5915.1997.tb01316.x text/html Verlag Deutschlandweit zugänglich Volltext GBV_USEFLAG_U ZDB-1-DJB GBV_NL_ARTICLE AR 28 1997 2 0 |
allfields_unstemmed |
10.1111/j.1540-5915.1997.tb01316.x doi (DE-627)NLEJ242482112 DE-627 ger DE-627 rakwb Smelcer, John B. verfasserin aut The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps Oxford, UK Blackwell Publishing Ltd 1997 Online-Ressource nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Geographic Information Systems (GIS) enable decision makers to view tabular data geographically, as maps. This simple yet powerful visual format appears to facilitate problem solving, yet how it does so is not clear, nor do we know the types of problems that benefit from this representation. To begin to understand the contributions of geographic representations over tabular representations, we conducted a three-factor experiment in problem solving. The experiment contained two different representations (map and table), three different geographic relationships (proximity, adjacency, and containment), and three levels of task difficulty (low, medium, and high). We found that maps generally produced faster problem solving than tables, and that problem-solving time increased with task difficulty. Most importantly, for the proximity and adjacency geographic relationships we found that maps kept problem-solving time low, while tables tended to increase time dramatically. However, we found that the number of knowledge states for each task explains performance times quite well and is a useful tool for understanding performance differences and interaction effects. As tasks become more difficult, representing them as maps generally keeps the number of knowledge states small, while for tables, the number of knowledge states increases dramatically. Correspondingly, problem-solving times increase dramatically with tables, but not with maps.In sum, as difficulty increases, maps are more effective for problem-solving tasks. Using maps, the tasks are simplified using visual heuristics that keep problemsolving times and error rates from rising as quickly as they do with tables. 2007 Blackwell Publishing Journal Backfiles 1879-2005 |2007|||||||||| Geographical Information System (GIS) Carmel, Erran verfasserin aut In Decision sciences Oxford : Wiley-Blackwell, 1988 28(1997), 2, Seite 0 Online-Ressource (DE-627)NLEJ243926456 (DE-600)2066218-X 1540-5915 nnns volume:28 year:1997 number:2 pages:0 http://dx.doi.org/10.1111/j.1540-5915.1997.tb01316.x text/html Verlag Deutschlandweit zugänglich Volltext GBV_USEFLAG_U ZDB-1-DJB GBV_NL_ARTICLE AR 28 1997 2 0 |
allfieldsGer |
10.1111/j.1540-5915.1997.tb01316.x doi (DE-627)NLEJ242482112 DE-627 ger DE-627 rakwb Smelcer, John B. verfasserin aut The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps Oxford, UK Blackwell Publishing Ltd 1997 Online-Ressource nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Geographic Information Systems (GIS) enable decision makers to view tabular data geographically, as maps. This simple yet powerful visual format appears to facilitate problem solving, yet how it does so is not clear, nor do we know the types of problems that benefit from this representation. To begin to understand the contributions of geographic representations over tabular representations, we conducted a three-factor experiment in problem solving. The experiment contained two different representations (map and table), three different geographic relationships (proximity, adjacency, and containment), and three levels of task difficulty (low, medium, and high). We found that maps generally produced faster problem solving than tables, and that problem-solving time increased with task difficulty. Most importantly, for the proximity and adjacency geographic relationships we found that maps kept problem-solving time low, while tables tended to increase time dramatically. However, we found that the number of knowledge states for each task explains performance times quite well and is a useful tool for understanding performance differences and interaction effects. As tasks become more difficult, representing them as maps generally keeps the number of knowledge states small, while for tables, the number of knowledge states increases dramatically. Correspondingly, problem-solving times increase dramatically with tables, but not with maps.In sum, as difficulty increases, maps are more effective for problem-solving tasks. Using maps, the tasks are simplified using visual heuristics that keep problemsolving times and error rates from rising as quickly as they do with tables. 2007 Blackwell Publishing Journal Backfiles 1879-2005 |2007|||||||||| Geographical Information System (GIS) Carmel, Erran verfasserin aut In Decision sciences Oxford : Wiley-Blackwell, 1988 28(1997), 2, Seite 0 Online-Ressource (DE-627)NLEJ243926456 (DE-600)2066218-X 1540-5915 nnns volume:28 year:1997 number:2 pages:0 http://dx.doi.org/10.1111/j.1540-5915.1997.tb01316.x text/html Verlag Deutschlandweit zugänglich Volltext GBV_USEFLAG_U ZDB-1-DJB GBV_NL_ARTICLE AR 28 1997 2 0 |
allfieldsSound |
10.1111/j.1540-5915.1997.tb01316.x doi (DE-627)NLEJ242482112 DE-627 ger DE-627 rakwb Smelcer, John B. verfasserin aut The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps Oxford, UK Blackwell Publishing Ltd 1997 Online-Ressource nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Geographic Information Systems (GIS) enable decision makers to view tabular data geographically, as maps. This simple yet powerful visual format appears to facilitate problem solving, yet how it does so is not clear, nor do we know the types of problems that benefit from this representation. To begin to understand the contributions of geographic representations over tabular representations, we conducted a three-factor experiment in problem solving. The experiment contained two different representations (map and table), three different geographic relationships (proximity, adjacency, and containment), and three levels of task difficulty (low, medium, and high). We found that maps generally produced faster problem solving than tables, and that problem-solving time increased with task difficulty. Most importantly, for the proximity and adjacency geographic relationships we found that maps kept problem-solving time low, while tables tended to increase time dramatically. However, we found that the number of knowledge states for each task explains performance times quite well and is a useful tool for understanding performance differences and interaction effects. As tasks become more difficult, representing them as maps generally keeps the number of knowledge states small, while for tables, the number of knowledge states increases dramatically. Correspondingly, problem-solving times increase dramatically with tables, but not with maps.In sum, as difficulty increases, maps are more effective for problem-solving tasks. Using maps, the tasks are simplified using visual heuristics that keep problemsolving times and error rates from rising as quickly as they do with tables. 2007 Blackwell Publishing Journal Backfiles 1879-2005 |2007|||||||||| Geographical Information System (GIS) Carmel, Erran verfasserin aut In Decision sciences Oxford : Wiley-Blackwell, 1988 28(1997), 2, Seite 0 Online-Ressource (DE-627)NLEJ243926456 (DE-600)2066218-X 1540-5915 nnns volume:28 year:1997 number:2 pages:0 http://dx.doi.org/10.1111/j.1540-5915.1997.tb01316.x text/html Verlag Deutschlandweit zugänglich Volltext GBV_USEFLAG_U ZDB-1-DJB GBV_NL_ARTICLE AR 28 1997 2 0 |
source |
In Decision sciences 28(1997), 2, Seite 0 volume:28 year:1997 number:2 pages:0 |
sourceStr |
In Decision sciences 28(1997), 2, Seite 0 volume:28 year:1997 number:2 pages:0 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
Geographical Information System (GIS) |
isfreeaccess_bool |
false |
container_title |
Decision sciences |
authorswithroles_txt_mv |
Smelcer, John B. @@aut@@ Carmel, Erran @@aut@@ |
publishDateDaySort_date |
1997-01-01T00:00:00Z |
hierarchy_top_id |
NLEJ243926456 |
id |
NLEJ242482112 |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">NLEJ242482112</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20210707155736.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">120427s1997 xx |||||o 00| ||und c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1111/j.1540-5915.1997.tb01316.x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)NLEJ242482112</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Smelcer, John B.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Oxford, UK</subfield><subfield code="b">Blackwell Publishing Ltd</subfield><subfield code="c">1997</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Geographic Information Systems (GIS) enable decision makers to view tabular data geographically, as maps. This simple yet powerful visual format appears to facilitate problem solving, yet how it does so is not clear, nor do we know the types of problems that benefit from this representation. To begin to understand the contributions of geographic representations over tabular representations, we conducted a three-factor experiment in problem solving. The experiment contained two different representations (map and table), three different geographic relationships (proximity, adjacency, and containment), and three levels of task difficulty (low, medium, and high). We found that maps generally produced faster problem solving than tables, and that problem-solving time increased with task difficulty. Most importantly, for the proximity and adjacency geographic relationships we found that maps kept problem-solving time low, while tables tended to increase time dramatically. However, we found that the number of knowledge states for each task explains performance times quite well and is a useful tool for understanding performance differences and interaction effects. As tasks become more difficult, representing them as maps generally keeps the number of knowledge states small, while for tables, the number of knowledge states increases dramatically. Correspondingly, problem-solving times increase dramatically with tables, but not with maps.In sum, as difficulty increases, maps are more effective for problem-solving tasks. Using maps, the tasks are simplified using visual heuristics that keep problemsolving times and error rates from rising as quickly as they do with tables.</subfield></datafield><datafield tag="533" ind1=" " ind2=" "><subfield code="d">2007</subfield><subfield code="f">Blackwell Publishing Journal Backfiles 1879-2005</subfield><subfield code="7">|2007||||||||||</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Geographical Information System (GIS)</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Carmel, Erran</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Decision sciences</subfield><subfield code="d">Oxford : Wiley-Blackwell, 1988</subfield><subfield code="g">28(1997), 2, Seite 0</subfield><subfield code="h">Online-Ressource</subfield><subfield code="w">(DE-627)NLEJ243926456</subfield><subfield code="w">(DE-600)2066218-X</subfield><subfield code="x">1540-5915</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:28</subfield><subfield code="g">year:1997</subfield><subfield code="g">number:2</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://dx.doi.org/10.1111/j.1540-5915.1997.tb01316.x</subfield><subfield code="q">text/html</subfield><subfield code="x">Verlag</subfield><subfield code="z">Deutschlandweit zugänglich</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-1-DJB</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_NL_ARTICLE</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">28</subfield><subfield code="j">1997</subfield><subfield code="e">2</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
series2 |
Blackwell Publishing Journal Backfiles 1879-2005 |
author |
Smelcer, John B. |
spellingShingle |
Smelcer, John B. misc Geographical Information System (GIS) The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps |
authorStr |
Smelcer, John B. |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)NLEJ243926456 |
format |
electronic Article |
delete_txt_mv |
keep |
author_role |
aut aut |
collection |
NL |
publishPlace |
Oxford, UK |
remote_str |
true |
illustrated |
Not Illustrated |
issn |
1540-5915 |
topic_title |
The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps Geographical Information System (GIS) |
publisher |
Blackwell Publishing Ltd |
publisherStr |
Blackwell Publishing Ltd |
topic |
misc Geographical Information System (GIS) |
topic_unstemmed |
misc Geographical Information System (GIS) |
topic_browse |
misc Geographical Information System (GIS) |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
zu |
hierarchy_parent_title |
Decision sciences |
hierarchy_parent_id |
NLEJ243926456 |
hierarchy_top_title |
Decision sciences |
isfreeaccess_txt |
false |
familylinks_str_mv |
(DE-627)NLEJ243926456 (DE-600)2066218-X |
title |
The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps |
ctrlnum |
(DE-627)NLEJ242482112 |
title_full |
The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps |
author_sort |
Smelcer, John B. |
journal |
Decision sciences |
journalStr |
Decision sciences |
isOA_bool |
false |
recordtype |
marc |
publishDateSort |
1997 |
contenttype_str_mv |
zzz |
container_start_page |
0 |
author_browse |
Smelcer, John B. Carmel, Erran |
container_volume |
28 |
physical |
Online-Ressource |
format_se |
Elektronische Aufsätze |
author-letter |
Smelcer, John B. |
doi_str_mv |
10.1111/j.1540-5915.1997.tb01316.x |
author2-role |
verfasserin |
title_sort |
the effectiveness of different representations for managerial problem solving: comparing tables and maps |
title_auth |
The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps |
abstract |
Geographic Information Systems (GIS) enable decision makers to view tabular data geographically, as maps. This simple yet powerful visual format appears to facilitate problem solving, yet how it does so is not clear, nor do we know the types of problems that benefit from this representation. To begin to understand the contributions of geographic representations over tabular representations, we conducted a three-factor experiment in problem solving. The experiment contained two different representations (map and table), three different geographic relationships (proximity, adjacency, and containment), and three levels of task difficulty (low, medium, and high). We found that maps generally produced faster problem solving than tables, and that problem-solving time increased with task difficulty. Most importantly, for the proximity and adjacency geographic relationships we found that maps kept problem-solving time low, while tables tended to increase time dramatically. However, we found that the number of knowledge states for each task explains performance times quite well and is a useful tool for understanding performance differences and interaction effects. As tasks become more difficult, representing them as maps generally keeps the number of knowledge states small, while for tables, the number of knowledge states increases dramatically. Correspondingly, problem-solving times increase dramatically with tables, but not with maps.In sum, as difficulty increases, maps are more effective for problem-solving tasks. Using maps, the tasks are simplified using visual heuristics that keep problemsolving times and error rates from rising as quickly as they do with tables. |
abstractGer |
Geographic Information Systems (GIS) enable decision makers to view tabular data geographically, as maps. This simple yet powerful visual format appears to facilitate problem solving, yet how it does so is not clear, nor do we know the types of problems that benefit from this representation. To begin to understand the contributions of geographic representations over tabular representations, we conducted a three-factor experiment in problem solving. The experiment contained two different representations (map and table), three different geographic relationships (proximity, adjacency, and containment), and three levels of task difficulty (low, medium, and high). We found that maps generally produced faster problem solving than tables, and that problem-solving time increased with task difficulty. Most importantly, for the proximity and adjacency geographic relationships we found that maps kept problem-solving time low, while tables tended to increase time dramatically. However, we found that the number of knowledge states for each task explains performance times quite well and is a useful tool for understanding performance differences and interaction effects. As tasks become more difficult, representing them as maps generally keeps the number of knowledge states small, while for tables, the number of knowledge states increases dramatically. Correspondingly, problem-solving times increase dramatically with tables, but not with maps.In sum, as difficulty increases, maps are more effective for problem-solving tasks. Using maps, the tasks are simplified using visual heuristics that keep problemsolving times and error rates from rising as quickly as they do with tables. |
abstract_unstemmed |
Geographic Information Systems (GIS) enable decision makers to view tabular data geographically, as maps. This simple yet powerful visual format appears to facilitate problem solving, yet how it does so is not clear, nor do we know the types of problems that benefit from this representation. To begin to understand the contributions of geographic representations over tabular representations, we conducted a three-factor experiment in problem solving. The experiment contained two different representations (map and table), three different geographic relationships (proximity, adjacency, and containment), and three levels of task difficulty (low, medium, and high). We found that maps generally produced faster problem solving than tables, and that problem-solving time increased with task difficulty. Most importantly, for the proximity and adjacency geographic relationships we found that maps kept problem-solving time low, while tables tended to increase time dramatically. However, we found that the number of knowledge states for each task explains performance times quite well and is a useful tool for understanding performance differences and interaction effects. As tasks become more difficult, representing them as maps generally keeps the number of knowledge states small, while for tables, the number of knowledge states increases dramatically. Correspondingly, problem-solving times increase dramatically with tables, but not with maps.In sum, as difficulty increases, maps are more effective for problem-solving tasks. Using maps, the tasks are simplified using visual heuristics that keep problemsolving times and error rates from rising as quickly as they do with tables. |
collection_details |
GBV_USEFLAG_U ZDB-1-DJB GBV_NL_ARTICLE |
container_issue |
2 |
title_short |
The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps |
url |
http://dx.doi.org/10.1111/j.1540-5915.1997.tb01316.x |
remote_bool |
true |
author2 |
Carmel, Erran |
author2Str |
Carmel, Erran |
ppnlink |
NLEJ243926456 |
mediatype_str_mv |
z |
isOA_txt |
false |
hochschulschrift_bool |
false |
doi_str |
10.1111/j.1540-5915.1997.tb01316.x |
up_date |
2024-07-06T02:09:04.256Z |
_version_ |
1803793721464979456 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">NLEJ242482112</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20210707155736.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">120427s1997 xx |||||o 00| ||und c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1111/j.1540-5915.1997.tb01316.x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)NLEJ242482112</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Smelcer, John B.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Oxford, UK</subfield><subfield code="b">Blackwell Publishing Ltd</subfield><subfield code="c">1997</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Geographic Information Systems (GIS) enable decision makers to view tabular data geographically, as maps. This simple yet powerful visual format appears to facilitate problem solving, yet how it does so is not clear, nor do we know the types of problems that benefit from this representation. To begin to understand the contributions of geographic representations over tabular representations, we conducted a three-factor experiment in problem solving. The experiment contained two different representations (map and table), three different geographic relationships (proximity, adjacency, and containment), and three levels of task difficulty (low, medium, and high). We found that maps generally produced faster problem solving than tables, and that problem-solving time increased with task difficulty. Most importantly, for the proximity and adjacency geographic relationships we found that maps kept problem-solving time low, while tables tended to increase time dramatically. However, we found that the number of knowledge states for each task explains performance times quite well and is a useful tool for understanding performance differences and interaction effects. As tasks become more difficult, representing them as maps generally keeps the number of knowledge states small, while for tables, the number of knowledge states increases dramatically. Correspondingly, problem-solving times increase dramatically with tables, but not with maps.In sum, as difficulty increases, maps are more effective for problem-solving tasks. Using maps, the tasks are simplified using visual heuristics that keep problemsolving times and error rates from rising as quickly as they do with tables.</subfield></datafield><datafield tag="533" ind1=" " ind2=" "><subfield code="d">2007</subfield><subfield code="f">Blackwell Publishing Journal Backfiles 1879-2005</subfield><subfield code="7">|2007||||||||||</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Geographical Information System (GIS)</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Carmel, Erran</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Decision sciences</subfield><subfield code="d">Oxford : Wiley-Blackwell, 1988</subfield><subfield code="g">28(1997), 2, Seite 0</subfield><subfield code="h">Online-Ressource</subfield><subfield code="w">(DE-627)NLEJ243926456</subfield><subfield code="w">(DE-600)2066218-X</subfield><subfield code="x">1540-5915</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:28</subfield><subfield code="g">year:1997</subfield><subfield code="g">number:2</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://dx.doi.org/10.1111/j.1540-5915.1997.tb01316.x</subfield><subfield code="q">text/html</subfield><subfield code="x">Verlag</subfield><subfield code="z">Deutschlandweit zugänglich</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-1-DJB</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_NL_ARTICLE</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">28</subfield><subfield code="j">1997</subfield><subfield code="e">2</subfield><subfield code="h">0</subfield></datafield></record></collection>
|
score |
7.4009905 |