Most recent issue published online in the International Journal of Information and Decision Sciences.
International Journal of Information and Decision Sciences
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International Journal of Information and Decision Sciences
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International Journal of Information and Decision Sciences
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http://www.inderscience.com/browse/index.php?journalID=306&year=2024&vol=16&issue=1
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D4SP - decision support system based on the use of the AHP method for science park selection
http://www.inderscience.com/link.php?id=136282
The literature reveals that science parks offer numerous benefits and support services to the activity of a technological startup. However, the decision of choosing the best science park for the startup tends to be an informal process, technically not very rigorous and planning, arising essentially by affinities with the research centre and university. In this study, a decision support system is presented to support entrepreneurs in the process of selecting a science park for the implementation of their startup. The AHP method is used to compare the importance of the criteria for selecting a science park, which includes factors such as location, activity sector, infrastructure, cost, and size. The findings reveal that the use of this decision support system helps entrepreneurs to find a science park that is suitable for the needs of their startup and allows them to comparatively identify the most relevant criteria when choosing a science park.
D4SP - decision support system based on the use of the AHP method for science park selection
Bruno Moura; Ivo Santos; Nelson Barros; Fernando Luis Almeida
International Journal of Information and Decision Sciences, Vol. 16, No. 1 (2024) pp. 1 - 18
The literature reveals that science parks offer numerous benefits and support services to the activity of a technological startup. However, the decision of choosing the best science park for the startup tends to be an informal process, technically not very rigorous and planning, arising essentially by affinities with the research centre and university. In this study, a decision support system is presented to support entrepreneurs in the process of selecting a science park for the implementation of their startup. The AHP method is used to compare the importance of the criteria for selecting a science park, which includes factors such as location, activity sector, infrastructure, cost, and size. The findings reveal that the use of this decision support system helps entrepreneurs to find a science park that is suitable for the needs of their startup and allows them to comparatively identify the most relevant criteria when choosing a science park.]]>
10.1504/IJIDS.2024.136282
International Journal of Information and Decision Sciences, Vol. 16, No. 1 (2024) pp. 1 - 18
Bruno Moura
Ivo Santos
Nelson Barros
Fernando Luis Almeida
Polytechnic Higher Institute of Gaya, Av. dos Descobrimentos, 333, 4400-103, V.N. Gaia, Portugal ' Polytechnic Higher Institute of Gaya, Av. dos Descobrimentos, 333, 4400-103, V.N. Gaia, Portugal ' Polytechnic Higher Institute of Gaya, Av. dos Descobrimentos, 333, 4400-103, V.N. Gaia, Portugal ' University of Porto, INESC TEC, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal
entrepreneurship
decision science
analytical hierarchy process
AHP
startups
new venture
science park
2024-01-26T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
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2024-01-26T23:20:50-05:00
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Soft skills fuzzy TOPSIS ranked multi-criteria to select project manager
http://www.inderscience.com/link.php?id=136280
This study aims to use fuzzy logic to select a project manager based on soft skills. In the first phase, a focus group interview was applied to establish the weights according to the soft skills list selected. In the second phase, the fuzzy TOPSIS logic was applied. According to the concept of the fuzzy TOPSIS, a closeness coefficient is defined to determine the ranking order of all alternatives. The results allowed the construction of the framework here called fuzzy TOPSIS ranked multi-criteria for selecting the best candidate according to the profile and criteria adopted. The contribution of this study is to allow the attribution of values to soft skills that, in essence, are subjectivity. This framework is friendly, the investment required is low, and it is adaptable to different contexts.
Soft skills fuzzy TOPSIS ranked multi-criteria to select project manager
Luciano Ferreira da Silva; Paulo Sergio Gonçalves de Oliveira; Gustavo Grander; Renato Penha; Flavio Santino Bizarrias
International Journal of Information and Decision Sciences, Vol. 16, No. 1 (2024) pp. 19 - 45
This study aims to use fuzzy logic to select a project manager based on soft skills. In the first phase, a focus group interview was applied to establish the weights according to the soft skills list selected. In the second phase, the fuzzy TOPSIS logic was applied. According to the concept of the fuzzy TOPSIS, a closeness coefficient is defined to determine the ranking order of all alternatives. The results allowed the construction of the framework here called fuzzy TOPSIS ranked multi-criteria for selecting the best candidate according to the profile and criteria adopted. The contribution of this study is to allow the attribution of values to soft skills that, in essence, are subjectivity. This framework is friendly, the investment required is low, and it is adaptable to different contexts.]]>
10.1504/IJIDS.2024.136280
International Journal of Information and Decision Sciences, Vol. 16, No. 1 (2024) pp. 19 - 45
Luciano Ferreira da Silva
Paulo Sergio Gonçalves de Oliveira
Gustavo Grander
Renato Penha
Flavio Santino Bizarrias
Nove de Julho University †UNINOVE, Deputado Salvador Julianelli Street, s/n †First Floor, Barra Funda, São Paulo/SP, 01156-080, Brazil ' Anhembi Morumbi University, Casa do Ator Street, 275 †Vila OlÃmpia, São Paulo/SP, 04546-001, Brazil ' Nove de Julho University †UNINOVE, Deputado Salvador Julianelli Street, s/n †First Floor, Barra Funda, São Paulo/SP, 01156-080, Brazil ' Nove de Julho University †UNINOVE, Deputado Salvador Julianelli Street, s/n †First Floor, Barra Funda, São Paulo/SP, 01156-080, Brazil ' Nove de Julho University †UNINOVE, Deputado Salvador Julianelli Street, s/n †First Floor, Barra Funda, São Paulo/SP, 01156-080, Brazil
fuzzy TOPSIS
multi-criteria decision
project manager selection
soft skill
human resources
competencies
competence
people management
project manager
2024-01-26T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
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45
2024-01-26T23:20:50-05:00
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Artificial neural networks in the development of business analytics projects
http://www.inderscience.com/link.php?id=136283
The accelerated evolution of information and communication technologies, with an ever-growing increase in their access and availability, has become the foundation for the current big data age. Business analytics (BAs) has helped different organisations leverage the large volumes of information available today. In fact, artificial neural networks (ANNs) provide deep data mining facilities to organisations for identifying patterns, predict probable future states, and fully benefit from predictions/forecasts. This article describes three ANNs application scenarios for the development of BA projects, by using network learning for: 1) executing accounting processes; 2) time series forecasts; 3) regression-based predictions. We validate scenarios by implementing an application-case using actual data, thus demonstrating the full extent of the capabilities of this technique. The main findings exhibit the expressive power of the programming languages used in data analytics, the wide range of tools/techniques available, and the impact these factors may have on the BA development projects.
Artificial neural networks in the development of business analytics projects
Juan Bernardo Quintero; David Villanueva-Valdes; Bell Manrique-Losada
International Journal of Information and Decision Sciences, Vol. 16, No. 1 (2024) pp. 46 - 72
The accelerated evolution of information and communication technologies, with an ever-growing increase in their access and availability, has become the foundation for the current big data age. Business analytics (BAs) has helped different organisations leverage the large volumes of information available today. In fact, artificial neural networks (ANNs) provide deep data mining facilities to organisations for identifying patterns, predict probable future states, and fully benefit from predictions/forecasts. This article describes three ANNs application scenarios for the development of BA projects, by using network learning for: 1) executing accounting processes; 2) time series forecasts; 3) regression-based predictions. We validate scenarios by implementing an application-case using actual data, thus demonstrating the full extent of the capabilities of this technique. The main findings exhibit the expressive power of the programming languages used in data analytics, the wide range of tools/techniques available, and the impact these factors may have on the BA development projects.]]>
10.1504/IJIDS.2024.136283
International Journal of Information and Decision Sciences, Vol. 16, No. 1 (2024) pp. 46 - 72
Juan Bernardo Quintero
David Villanueva-Valdes
Bell Manrique-Losada
Faculty of Engineering, EAFIT University, MedellÃn, Colombia ' Faculty of Engineering, University of MedellÃn, MedellÃn, Colombia ' Faculty of Engineering, University of MedellÃn, MedellÃn, Colombia
artificial neural networks
ANNs
business analytics
data analytics
big data
deep data mining
network learning process
time series forecast
regression-based prediction
activity-based costing
supervised learning
decision making
2024-01-26T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
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2024-01-26T23:20:50-05:00
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EOQ model for time dependent demand with deterioration, inflation, shortages and trade credits
http://www.inderscience.com/link.php?id=136278
The inflation acts an important role for each area of life in the world. Inflation varies rapidly for high tech commodities with passing over time. This study develops an EOQ model with time sensitive demand rate for deteriorating products and shortages with inflation over a predetermined planning horizon. Mathematical formulations are prepared under two cases: 1) time for positive inventory (<i>T</i><SUB align="right">1) is greater than credit period <i>M</i>; 2) <i>T</i><SUB align="right">1 is less than or equal to credit period <i>M</i>, to gain optimal number of replenishment and cycle time. An algorithm is presented to find the most favourable cycle time so that total annual relevant profit is maximised. We then demonstrate the total profit is concave with respect to number of replenishments. Numerical examples are offered to display the model. Sensitivity investigation for variation of a number of key parameters is also discussed. Mathematica 7.0 software is used to calculate numerical results and optimality conditions.
EOQ model for time dependent demand with deterioration, inflation, shortages and trade credits
R.P. Tripathi
International Journal of Information and Decision Sciences, Vol. 16, No. 1 (2024) pp. 73 - 89
The inflation acts an important role for each area of life in the world. Inflation varies rapidly for high tech commodities with passing over time. This study develops an EOQ model with time sensitive demand rate for deteriorating products and shortages with inflation over a predetermined planning horizon. Mathematical formulations are prepared under two cases: 1) time for positive inventory (<i>T</i><SUB align="right">1) is greater than credit period <i>M</i>; 2) <i>T</i><SUB align="right">1 is less than or equal to credit period <i>M</i>, to gain optimal number of replenishment and cycle time. An algorithm is presented to find the most favourable cycle time so that total annual relevant profit is maximised. We then demonstrate the total profit is concave with respect to number of replenishments. Numerical examples are offered to display the model. Sensitivity investigation for variation of a number of key parameters is also discussed. Mathematica 7.0 software is used to calculate numerical results and optimality conditions.]]>
10.1504/IJIDS.2024.136278
International Journal of Information and Decision Sciences, Vol. 16, No. 1 (2024) pp. 73 - 89
Juan Bernardo Quintero
David Villanueva-Valdes
Bell Manrique-Losada
Department of Applied Sciences and Humanities, KNIT, Sultanpur, UP, India Affiliated to Dr. A.P.J. Abdul Kalam Technical University, Lucknow, UP, India
cash flow
inflation
non-increasing demand
credit period
shortages
2024-01-26T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
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89
2024-01-26T23:20:50-05:00
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A GIS-based framework for flood hazard vulnerability evaluation in Thudawa area, Sri Lanka
http://www.inderscience.com/link.php?id=136281
The objectives of our research were identifying and classifying flood risk areas into different classes in Thudawa area, Sri Lanka, and developing a geographical information system (GIS) model to identify flood vulnerability areas accurately in Thudawa area. It was expected to propose preventive guidelines of flood hazard vulnerability using geo-informatics. The methodological procedure is extremely important in this type of research thus, the spatial multi-criteria decision analysis (MCDA) procedure was used. For this research, analytical hierarchy process (AHP) was used for the criterion weighting. AHP calculations run upon the results of experts' judgment as proposed by the Satty incorporating pair-wise comparison method. The results of this study attempt to analyse the existing flash flood risk levels using the GIS-based multi-criteria analysis technique which allowed ranking of risk areas since it is important in the decision-making process to mitigate the flood risk in the study area.
A GIS-based framework for flood hazard vulnerability evaluation in Thudawa area, Sri Lanka
M.W.R. Nuwanka; W.K.N.C. Withanage
International Journal of Information and Decision Sciences, Vol. 16, No. 1 (2024) pp. 90 - 108
The objectives of our research were identifying and classifying flood risk areas into different classes in Thudawa area, Sri Lanka, and developing a geographical information system (GIS) model to identify flood vulnerability areas accurately in Thudawa area. It was expected to propose preventive guidelines of flood hazard vulnerability using geo-informatics. The methodological procedure is extremely important in this type of research thus, the spatial multi-criteria decision analysis (MCDA) procedure was used. For this research, analytical hierarchy process (AHP) was used for the criterion weighting. AHP calculations run upon the results of experts' judgment as proposed by the Satty incorporating pair-wise comparison method. The results of this study attempt to analyse the existing flash flood risk levels using the GIS-based multi-criteria analysis technique which allowed ranking of risk areas since it is important in the decision-making process to mitigate the flood risk in the study area.]]>
10.1504/IJIDS.2024.136281
International Journal of Information and Decision Sciences, Vol. 16, No. 1 (2024) pp. 90 - 108
M.W.R. Nuwanka
W.K.N.C. Withanage
Department of Geography, Faculty of Humanities and Social Sciences, University of Ruhuna, Matara, 81000, Sri Lanka ' Department of Geography, Faculty of Humanities and Social Sciences, University of Ruhuna, Matara, 81000, Sri Lanka
analytical hierarchy process
AHP
flood hazard
geographical information system
GIS
spatial multi-criteria decision analysis
MCDA
modelling
Sri Lanka
2024-01-26T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
16
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90
108
2024-01-26T23:20:50-05:00