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...
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| Autor*in: |
Smelcer, John B. [verfasserIn] Carmel, Erran [verfasserIn] |
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| Format: |
E-Artikel |
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| Erschienen: |
Oxford, UK: Blackwell Publishing Ltd ; 1997 |
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| Umfang: |
Online-Ressource |
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| Reproduktion: |
2007 ; Blackwell Publishing Journal Backfiles 1879-2005 |
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| Übergeordnetes Werk: |
In: Decision sciences - Oxford : Wiley-Blackwell, 1988, 28(1997), 2, Seite 0 |
| Übergeordnetes Werk: |
volume:28 ; year:1997 ; number:2 ; pages:0 |
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| DOI / URN: |
10.1111/j.1540-5915.1997.tb01316.x |
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| 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. | ||
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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 |
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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 |
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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 |
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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 |
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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. |
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The Effectiveness of Different Representations for Managerial Problem Solving: Comparing Tables and Maps |
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