GeoComputation and Spatial Modelling for Decision-Making

2021 ◽  
pp. 221-273
Author(s):  
Gouri Sankar Bhunia ◽  
Pravat Kumar Shit
Keyword(s):  
Decision Making ◽  
Spatial Modelling

scholarly journals Quantitative versus Qualitative Geospatial Data in Spatial Modelling and Decision Making

2012 ◽  
Vol 04 (03) ◽  
pp. 237-241 ◽  
Author(s):  
Ko Ko Lwin ◽  
Yuji Murayama ◽  
Chiaki Mizutani
Keyword(s):  
Decision Making ◽  
Spatial Modelling ◽  
Geospatial Data

scholarly journals Spatial modelling of assumption of tourism development with geographic IT using

2010 ◽  
Vol 58 (6) ◽  
pp. 279-294
Author(s):  
Jitka Machalová ◽  
Ida Vajčnerová ◽  
Kateřina Ryglová
Keyword(s):  
Decision Making ◽  
Czech Republic ◽  
Information Technologies ◽  
Tourism Development ◽  
Spatial Modelling ◽  
Capital City ◽  
Geographical Information ◽  
The Czech Republic ◽  
Decision Making Processes ◽  
High Level

The aim of this article is to show the possibilities of spatial modelling and analysing of assumptions of tourism development in the Czech Republic with the objective to make decision-making processes in tourism easier and more efficient (for companies, clients as well as destination managements). The development and placement of tourism depend on the factors (conditions) that influence its application in specific areas. These factors are usually divided into three groups: selective, localization and realization. Tourism is inseparably connected with space – countryside. The countryside can be modelled and consecutively analysed by the means of geographical information technologies. With the help of spatial modelling and following analyses the localization and realization conditions in the regions of the Czech Republic have been evaluated. The best localization conditions have been found in the Liberecký region. The capital city of Prague has negligible natural conditions; however, those social ones are on a high level. Next, the spatial analyses have shown that the best realization conditions are provided by the capital city of Prague. Then the Central-Bohemian, South-Moravian, Moravian-Silesian and Karlovarský regions follow. The development of tourism destination is depended not only on the localization and realization factors but it is basically affected by the level of local destination management. Spatial modelling can help destination managers in decision-making processes in order to optimal use of destination potential and efficient targeting their marketing activities.

scholarly journals The specification of consumer satisfaction in tourism with the use of geographic IT tools

2010 ◽  
Vol 58 (6) ◽  
pp. 433-444 ◽  
Author(s):  
Kateřina Ryglová ◽  
Jitka Machalová ◽  
Ida Vajčnerová
Keyword(s):  
Decision Making ◽  
Customer Satisfaction ◽  
Detailed Analysis ◽  
Consumer Satisfaction ◽  
Measurement Model ◽  
Spatial Modelling ◽  
Competitive Environment ◽  
Decision Making Processes ◽  
Tourism Services

Tourism is globally considered to be one of the most prospective and dynamic economic branches. However, with respect to highly competitive environment of tourism it has to be professionally organized and managed. The presented article aims to show possibilities of interconnecting marketing tools with the potential of spatial modelling with the objective of making decision-making processes in tourism easier and more efficient (for companies, clients as well as destination managements). The paper deals with the modification of the customer satisfaction measurement model in tourism with possibilities of spatial modelling tools. In the publication the ECSI model (European Customer Sa­tisfaction Index) is modified for the area of tourism, with respect to the fact that the obtained ­values of ECSI indexes can be utilized as introductory data for spatial modelling. The potential of the ECSI utilization is seen as a tool for managing decision-making processes in the area of increasing the quali­ty of tourism services by force of a detailed analysis and quantification of customer satisfaction. If we process the date about satisfaction from monitoring CzechTourism, and if we apply the use date on described ESCI model (the part satisfaction), we see, that the visitors are the most satisfaction with helpfulness (interval 73−87 %), namely in South-Bohemian, South-Moravian, and Zlin region, at least in Midle-Bohemian region. Obtaining own data and their following application and evaluation according to the modified ESCI model for all tourist regions will be the part of a follow-up research. The aim will be to summarize recommendations for individual regions in such a way that they have enough information for more successful utilization of their potential for the development of tourism.

Discarding optimality: Throwing out the baby with the bathwater?

2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Reward Rate ◽  
Perceptual Decision ◽  
Standard Observer ◽  
Rate Maximization ◽  
Reward Rate Maximization ◽  
Descriptive Standard ◽  
Observer Model

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.

LPCD framework: Analytical tool or psychological model?

2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks
Keyword(s):  
Decision Making ◽  
Analytical Tool ◽  
Mathematical Framework ◽  
Bayesian Decision ◽  
Perceptual Decision Making ◽  
Psychological Model ◽  
Psychological Reality ◽  
Psychological Theories ◽  
Target Article ◽  
Bayesian Decision Making

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.

Elaborating the role of reflection and individual differences in the study of folk-economic beliefs

2018 ◽  
Vol 41 ◽  
Author(s):  
Kevin Arceneaux
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Cognitive Processes ◽  
Evolutionary History ◽  
Behavioral Responses ◽  
History Of ◽  
Economic Beliefs

AbstractIntuitions guide decision-making, and looking to the evolutionary history of humans illuminates why some behavioral responses are more intuitive than others. Yet a place remains for cognitive processes to second-guess intuitive responses – that is, to be reflective – and individual differences abound in automatic, intuitive processing as well.

The primacy of conscious decision making – ERRATUM

2014 ◽  
Vol 38 (01) ◽  
pp. 46
Author(s):  
David R. Shanks ◽  
Ben R. Newell
Keyword(s):  
Decision Making ◽  
Conscious Decision

The primacy of conscious decision making – RETRACTION

2014 ◽  
Vol 38 (01) ◽  
pp. 48
Author(s):  
David R. Shanks ◽  
Ben R. Newell
Keyword(s):  
Decision Making ◽  
Conscious Decision

Abstraction: An alternative neurocognitive account of recognition, prediction, and decision making

2020 ◽  
Vol 43 ◽  
Author(s):  
Valerie F. Reyna ◽  
David A. Broniatowski
Keyword(s):  
Decision Making ◽  
Software Engineering ◽  
Systems Engineering ◽  
Evidence Based ◽  
Extensive Literature ◽  
Trace Theory ◽  
Fuzzy Trace Theory ◽  
Abstract Representations ◽  
Technical Systems

Abstract Gilead et al. offer a thoughtful and much-needed treatment of abstraction. However, it fails to build on an extensive literature on abstraction, representational diversity, neurocognition, and psychopathology that provides important constraints and alternative evidence-based conceptions. We draw on conceptions in software engineering, socio-technical systems engineering, and a neurocognitive theory with abstract representations of gist at its core, fuzzy-trace theory.

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