Dynamic SWOT analysis as a tool for ROMS

Jasinevičius, Raimundas; Petrauskas, Vytautas

doi:10.1109/baltic.2006.7266129

Cited by 7 publications

(8 citation statements)

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Section: The Swot Engine_net Levelmentioning

confidence: 74%

“…Results (6) and (7) ( a , a are comparable and can develop further consideration, but only after their normalization. It is obvious that this normalization can be achieved by involving coefficients of normalization (8) and (9) for threats and opportunities correspondingly: The remark positive means that only positive auxiliary flags are taken into account in all those sums as potentially capable to create maximal value of threats and possibilities according to (6) and (7). The coefficients for the normalization of (8) and (9) are determined after the analysis of (6) and (7), keeping in mind the fact that the maximal value of the summarized and normalized threat and of the summarized and normalized opportunity must not exceed 1.…”

Section: The Swot Engine_net Levelmentioning

confidence: 74%

“…This paper: 1) introduces and expands the dynamic approach to SWOT analysis as it was firstly proposed in [5] and [6], using the mechanism of dynamic fuzzy cognitive maps; 2) introduces the possibility of using quantitative and qualitative input and output data as well as to the verbal SWOT reasoning, using the paradigm of computing with words (CWW) as was firstly proposed for such procedure in [8]; 3) provides SWOT expert teams with the support tools for reasoning and decision making using fuzzy risk analysis, following the risk paradigm presented in [9], which methodologically corresponds to the conclusions provided in [7]. The definition, assessment, and management remains shaky and unfounded in general, so we selected and invented our own metrics for fuzzy risk with the aim of making them useful for decision makers in SWOT analysis.…”

Section: Introductionmentioning

confidence: 99%

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Concept of a System Using a Dynamic SWOT Analysis Network for Fuzzy Control of Risk in Complex Environments

Petrauskas¹,

Jasinevičius²,

Kazanavičius³

et al. 2020

MCS

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The paper advocates a new concept for risk control that makes up one organic closed loop feedback system, with the following stages: 1) the evaluation of the positive and negative features of situation under investigation through strengths, weaknesses, opportunities, and threats (SWOT) analysis, 2) the determination of the level of fuzzy risk concealed in this situation (using RISK evaluation), and 3) the proposal of leverage, recommendations, or actions (through LEVERAGE aggregation) enabling the improvement of target performance. Useful fundamental approaches, definitions, and particularities of this concept concerning SWOT, RISK and LEVERAGES are examined, and for the first time the network type called here the fuzzy SWOT map (FSM) is introduced. This newly proposed instrument appeared as a result of a natural extension of fuzzy cognitive maps paradigm enhanced by dynamic computing with words (CWW) elements and possibilities to use the explainable artificial intelligence (XAI) in the form of fuzzy inference rules. The concept serves for development of functional organization of control systems of complex and dynamically interacting projects or situations and for implementation of adequate set of tools satisfying the concrete system's requirements. The results of conceptual modeling and the confirmation of the vitality of the approach are presented based on the simplified example of a risk-control system case covering three interacting projects in a complex environment of city development.

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Section: The Swot Engine_net Levelmentioning

confidence: 74%

Section: The Swot Engine_net Levelmentioning

confidence: 74%

Section: Introductionmentioning

confidence: 99%

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Concept of a System Using a Dynamic SWOT Analysis Network for Fuzzy Control of Risk in Complex Environments

Petrauskas¹,

Jasinevičius²,

Kazanavičius³

et al. 2020

MCS

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“…Nowadays, the use of SWOT analysis is continually growing (Ayub, Razzaq, Aslam, & Iftekhar, 2013;Coman & Ronen, 2009;Fine, 2010;Ghazinoory, Abdi, & Azadegan-Mehr, 2011;Jasinevičius & Petrauskas, 2015;Shahmirzadi, 2017;Simoneaux & Stroud, 2011). SWOT analysis, whose creation and diffusion in theory and practice cannot be attributed to a single author, was developed mostly after the mid-20th century and, since then, it is one of the most popular approaches in the strategic management of organizations (King, 2004).…”

Section: The Positioning Of the Problem: The Shortcomings Of The Convmentioning

confidence: 99%

Towards a Restructuration of the Conventional SWOT Analysis

Vlados

2019

BMS

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Today, the use of SWOT analysis is increasingly popular for the strategic planning of businesses. However, we argue that a traditional and conventional way of approaching the SWOT analysis contains an interpretative mistargeting which, in the background, derives from the absence of a comprehensive evolutionary methodological framework. Therefore, a conventional SWOT analysis that articulates lists of strengths-weaknesses and opportunities-threats in an absolute and non-correlative way is probably inappropriate to give answers to the needs of strategic planning. In this direction, by also exploring elements from the criticism to the traditional SWOT analysis, we counter-propose a new conceptual framework that perceives SWOT analysis in a correlative and evolutionary way, for all the kinds of socioeconomic organisms.

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“…Up till now tools, based on fuzzy cognitive maps (FCM) and dynamic Strengths -WeaknessesOpportunities -Threats (SWOT) analysis, were used for such a decision making and the evaluation of consequences ([5]- [7]). …”

Section: Introductionmentioning

confidence: 99%

Fuzzy expert maps for risk management systems

Jasinevičius

Petrauskas

2008

2008 IEEE/OES US/EU-Baltic International Symposium

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After widely known implementations of perfect ideas, expressed by researchers R. Axelrod, L. Zadeh and B. Kosko, the fuzzy cognitive map (FCM) became an important tool for decision makers in various practical areas, such as business evaluation, risk management, international policy making, medical diagnostics and other [5]. The principle possibility of FCM involvement into regional oceanic modeling system (ROMS) was presented during the US/EU Baltic International Symposium in Klaipeda in May 2006 [12]. Today's experience permits to extend the concept of FCM nodes, including additional fuzzy expert knowledge and enriching the representation of real situations under consideration. This paper presents a systematic approach, based on the authors' research, to the idea of FCM extension and its transformation into a rule-based fuzzy expert map (FEM), presents a simplified fragment of FEM use for a port security system, and discusses further perspectives of developing new tools for decision makers in risk management systems in general.

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Dynamic SWOT analysis as a tool for ROMS

Cited by 7 publications

References 0 publications

Concept of a System Using a Dynamic SWOT Analysis Network for Fuzzy Control of Risk in Complex Environments

Concept of a System Using a Dynamic SWOT Analysis Network for Fuzzy Control of Risk in Complex Environments

Towards a Restructuration of the Conventional SWOT Analysis

Fuzzy expert maps for risk management systems

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