Augmented fuzzy cognitive maps for modelling LMS critical success factors

Salmeron, Jose L.

doi:10.1016/j.knosys.2009.01.002

Cited by 112 publications

(64 citation statements)

References 11 publications

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“…Ferreira, Jalali, J. Ferreira, Stankevičienė, & Marques, 2016b). The cause-and-effect relationships between the concepts can then take on three different forms, depending on the type of influence one concept exerts on the other: (1) positive causality, when an increase in the value of one concept leads to an increase in the value of another concept; (2) negative causality, when an increase in the value of one concept leads to a decrease in the value of another concept; and (3) lack of causality, when two concepts do not influence each other (Salmeron, 2009). Figure 1 exemplifies an FCM.…”

Section: Cognitive Maps and Fuzzy Cognitive Mapsmentioning

confidence: 99%

Barriers to Real Estate Investments for Residential Rental Purposes: Mapping Out the Problem

Pires

Ferreira

Jalali

et al. 2018

International Journal of Strategic Property Management

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Abstract. The recent economic crisis led to significant changes in the real estate market; one of which was a shift toward home rental (rather than buying). Real estate investors have an important role in the growth of the rental market. However, there are often hindrances to investing for residential rental purposes. In order to overcome these barriers, they first need to be identified and understood. With this in mind, the main focus of this investigation was the creation of a conceptual model, through fuzzy cognitive mapping, to identify and understand the cause-and-effect relationships between the factors that represent an obstacle to real estate investments for residential rental purposes. The results show that cognitive maps can be of great use for the structuring of complex decision problems, minimizing the number of factors left out of the decision-making process. In particular, the tenant risk behavior, property location and associated costs (for the owner) were identified as the main obstacles to real estate investment. The practical implications of the model, as well as the advantages and limitations of the process followed, are also discussed.

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Section: Cognitive Maps and Fuzzy Cognitive Mapsmentioning

confidence: 99%

Barriers to Real Estate Investments for Residential Rental Purposes: Mapping Out the Problem

Pires

Ferreira

Jalali

et al. 2018

International Journal of Strategic Property Management

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“…Carlucci et al 2013). This type of cognitive mapping has since been applied in a wide range of different decision situations (an extensive deliberation falls outside of the scope of this paper; but for further discussion, see Tsadiras et al 2003;Kok 2009;Salmeron 2009;Yaman and Polat 2009;Papageorgiou et al 2012;Salmeron 2012).…”

Section: Background On Fuzzy Cognitive Mappingmentioning

confidence: 99%

Understanding the dynamics behind bank branch service quality in Portugal: pursuing a holistic view using fuzzy cognitive mapping

et al. 2015

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Using fuzzy cognitive mapping, this study aims to create a holistic framework whereby the determinants of bank branch service quality and their cause-and-effect relationships can be identified and dynamically analyzed. The methodology is applied using a group of experts from the banking industry in Portugal. Our results not only indicate the applicability and usefulness of the proposed approach, but identify human resource characteristics (which include collaborators' personal and professional training) and management team technical skills as particularly relevant driving forces of bank branch service quality. The proposal holds great potential for the operational planning and improvement of bank branch service quality, which is a prime concern for bank administrators, bank branch collaborators, and society at large. Advantages and shortcomings of the framework are also reported.

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“…Some other reported methods, like [115] and [116] have extended classical ones, in order to accommodate for the credibility factors of individual maps, by replacing the ordinary average with a weighted average. The weights w i are assigned to experts proportionally to their reliability and take values from range [0,1].…”

Section: Co-published By Atlantis Press and Taylor And Francis Copyrighmentioning

confidence: 99%

Tackling Travel Behaviour: An approach based on Fuzzy Cognitive Maps

León¹,

Nápoles²,

Bello³

et al. 2013

IJCIS

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Although the individuals" transport behavioural modelling is a complex task, it can produce a notable social and economic impact. In this paper, Fuzzy Cognitive Maps are explored to represent the behaviour and operation of such complex systems. An automatic approach to extract mental representations from individuals and convert them into computational structures is defined. For the creation of knowledge bases the use of Knowledge Engineering is accounted and later on the data is transferred into structures based on Fuzzy Cognitive Maps. Once the maps are created, their performances get improved through the use of a Particle Swarm Optimisation algorithm as a learning method, readjusting its predicting capacity from stored scenarios, where individuals left their preferences in front of random situations. Another important result is clustering the maps for knowledge discovery. This permits to find useful groups of individuals that policymakers can use for simulating new rules and policies. After related maps are identified, to merge them as a unique structure could benefit for different usages. Therefore an aggregating procedure is elaborated for this task, constituting an alternative approach for selecting a centroid of a specific estimated group, and therefore having, in only one structure, the knowledge and behavioural acting from a collection of individuals. Learning, clustering and aggregation of Fuzzy Cognitive Maps are combined in a cascade experiment, with the intention of describing travellers" behaviour and change trends in different abstraction levels. The results of this approach will help transportation policy decision makers to understand the people"s needs in a better way, consequently will help them actualising different policy formulations and implementations.

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Augmented fuzzy cognitive maps for modelling LMS critical success factors

Cited by 112 publications

References 11 publications

Barriers to Real Estate Investments for Residential Rental Purposes: Mapping Out the Problem

Barriers to Real Estate Investments for Residential Rental Purposes: Mapping Out the Problem

Understanding the dynamics behind bank branch service quality in Portugal: pursuing a holistic view using fuzzy cognitive mapping

Tackling Travel Behaviour: An approach based on Fuzzy Cognitive Maps

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