A fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEs
Advances in technology and an increase in the amount and complexity of data that are generated in healthcare have led to an indispensable revolution in this sector related to big data. Analytics of information based on multimodal clinical data sources requires big data projects. When starting big da...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2019
- Institución:
- Universidad de Medellín
- Repositorio:
- Repositorio UDEM
- Idioma:
- eng
- OAI Identifier:
- oai:repository.udem.edu.co:11407/5757
- Acceso en línea:
- http://hdl.handle.net/11407/5757
- Palabra clave:
- Big data
ELECTRE method
Fuzzy methods
Healthcare
Maturity level
Outranking
Decision making
Health care
Information management
Clinical data
Electre methods
Fuzzy methods
Healthcare sectors
Maturity levels
Multi criteria decision making
Outranking
Small and medium sized enterprise
Big data
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- License
- http://purl.org/coar/access_right/c_16ec
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A fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEs |
| title |
A fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEs |
| spellingShingle |
A fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEs Big data ELECTRE method Fuzzy methods Healthcare Maturity level Outranking Decision making Health care Information management Clinical data Electre methods Fuzzy methods Healthcare sectors Maturity levels Multi criteria decision making Outranking Small and medium sized enterprise Big data |
| title_short |
A fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEs |
| title_full |
A fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEs |
| title_fullStr |
A fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEs |
| title_full_unstemmed |
A fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEs |
| title_sort |
A fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEs |
| dc.subject.none.fl_str_mv |
Big data ELECTRE method Fuzzy methods Healthcare Maturity level Outranking Decision making Health care Information management Clinical data Electre methods Fuzzy methods Healthcare sectors Maturity levels Multi criteria decision making Outranking Small and medium sized enterprise Big data |
| topic |
Big data ELECTRE method Fuzzy methods Healthcare Maturity level Outranking Decision making Health care Information management Clinical data Electre methods Fuzzy methods Healthcare sectors Maturity levels Multi criteria decision making Outranking Small and medium sized enterprise Big data |
| description |
Advances in technology and an increase in the amount and complexity of data that are generated in healthcare have led to an indispensable revolution in this sector related to big data. Analytics of information based on multimodal clinical data sources requires big data projects. When starting big data projects in the healthcare sector, it is often necessary to assess the maturity of an organization with respect to big data, i.e., its capacity in managing big data. The assessment of the maturity of an organization requires multicriteria decision making as there is no single criterion or dimension that defines the maturity level regarding big data but an entire set of them. Based on the ISO 15504, this article proposes a fuzzy ELECTRE structure methodology to assess the maturity level of small- and medium-sized enterprises in the healthcare sector. The obtained experimental results provide evidence that this methodology helps to determine and compare maturity levels in big data management of organizations or the evolution of maturity over time. This is also useful in terms of diagnosing the readiness of an organization before starting to implement big data initiatives or technologies. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature. |
| publishDate |
2019 |
| dc.date.accessioned.none.fl_str_mv |
2020-04-29T14:53:54Z |
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2020-04-29T14:53:54Z |
| dc.date.none.fl_str_mv |
2019 |
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Article |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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http://purl.org/coar/resource_type/c_6501 http://purl.org/coar/resource_type/c_2df8fbb1 |
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14327643 |
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http://hdl.handle.net/11407/5757 |
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10.1007/s00500-018-3625-8 |
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14327643 10.1007/s00500-018-3625-8 |
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http://hdl.handle.net/11407/5757 |
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eng |
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eng |
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Angilella, S., Mazzu, S., The financing of innovative SMEs: a multicriteria credit rating model (2015) Eur J Oper Res, 244 (2), pp. 540-554 Anún, J.P., Alarcón, R., Ranking projects of logistics platforms: a methodology based on the electre multicriteria approach (2014) Proc Soc Behav Sci, 160, pp. 5-14 Bana e Costa, C.A., (1990) Readings in multiple criteria decision aid, , Springer, Berlin Benayoun, R., Roy, B., Sussmann, B., (1966) ELECTRE: Une méthode Pour Guider Le Choix En présence De Points De Vue Multiples, Note De Travail N ? 49 De La Direction Scientifique De La SEMA Bodas-Sagi, D.J., Labeaga Big, J.M., Data and health economics: opportunities, challenges and risks (2018) Int J Interact Multimed Artif Intell, 4 (7), pp. 47-52 Bouyssou, D., Marchant, T., An axiomatic approach to noncompensatory sorting methods in MCDM, I: the case of two categories (2007) Eur J Oper Res, 178 (1), pp. 217-245 Brans, J.-P., De Smet, Y., PROMETHEE methods (2016) Multiple criteria decision analysis. International series in operations research & management science, 233, pp. 187-219. , Greco S, Ehrgott M, Figueira J, (eds), Springer, New York Cabrerizo, F.J., Al-Hmouz, R., Morfeq, A., Balamash, A.S., Martínez, M.A., Herrera-Viedma, E., Soft consensus measures in group decision making using unbalanced fuzzy linguistic information (2017) Soft Comput, 21 (11), pp. 3037-3050 Camba, J.D., Contero, M., Company, P., Parametric CAD modeling: an analysis of strategies for design reusability (2016) Comput-Aided Des, 74, pp. 18-31 Capuano, N., Chiclana, F., Fujita, H., Herrera-Viedma, E., Loia, V., Fuzzy group decision making with incomplete information guided by social influence (2018) IEEE Trans Fuzzy Syst, 26 (3), pp. 1704-1718 Chandarana, P., Vijayalakshmi, M., Big data analytics frameworks (2014) Proceedings of the 2014 International Conference on Circuits, Systems, Communication and Information Technology Applications (CSCITA), pp. 430-434. , Mumbai Dehe, B., Bamford, D., Development, test and comparison of two multiple criteria decision analysis (MCDA) models: a case of healthcare infrastructure location (2015) Exp Syst Appl, 42 (19), pp. 6717-6727 Díaz-Ley, M., García, F., Piattini, M., MIS-PyME software measurement capability maturity model supporting the definition of software measurement programs and capability determination (2010) Adv Eng Softw, 41 (10-11), pp. 1223-1237 Dong, Y., Li, C.-C., Chiclana, F., Herrera-Viedma, E., Average-case consistency measurement and analysis of interval-valued reciprocal preference relations (2016) Knowl-Based Syst, 114, pp. 108-117 Dong, Y., Liu, W., Chiclana, F., Herrera-Viedma, E., Cabrerizo, F.J., Group decision-making based on heterogeneous preference relations with self-confidence (2017) Fuzzy Optim Decis Mak, 16 (4), pp. 429-447 Eric, J.-L., An application of the UTA discriminant model for the evaluation of R & D projects (1995) Advances in multicriteria analysis. Nonconvex optimization and its applications, 5. , Pardalos PM, Siskos Y, Zopounidis C, (eds), Springer, Boston Figueira, J., Roy, B., Determining the weights of criteria in the ELECTRE type methods with a revised Simos procedure (2002) Eur J Oper Res, 139 (2), pp. 317-326 Figueira, J.R., Mousseau, V., Roy, B., ELECTRE methods (2016) Multiple criteria decision analysis. International series in operations research & management science, 233, pp. 155-182. , Greco S, Ehrgott M, Figueira J, (eds), Springer, New York Garousi, V., Felderer, M., Hacaloglu, T., Software test maturity assessment and test process improvement: a multivocal literature review (2017) Inf Softw Technol, 85, pp. 16-42 Garzás, J., Pino, F.J., Piattini, M., Fernández, C.M., A maturity model for the Spanish software industry based on ISO standards (2013) Comput Stand Interf, 35 (6), pp. 616-628 Goksen, Y., Cevik, E., Avunduk, H., A case analysis on the focus on the maturity models and information technologies (2015) Proc Econ Fin, 19, pp. 208-216 González-Ferrer, A., Seara, G., Cháfer, J., Mayol, J., Generating big data sets from knowledge-based decision support systems to pursue value-based healthcare (2018) Int J Interact Multimed Artif Intell, 4 (7), pp. 42-46 Görög, M., A broader approach to organisational project management maturity assessment (2016) Int J Proj Manag, 34 (8), pp. 1658-1669 (2017) Healthcare Smes Lead the Way with GS1 Standards, , https://www.gs1ie.org/Healthcare/Resources/Case-Studies/Healthcare-SMEs-Lead-the-Way-with-GS1-Standards.html Halper, F., Stoler, D., (2014) TDWI Analytics Maturity Model Guide Transforming Data with Intelligence, , https://tdwi.org/whitepapers/2014/10/tdwi-analytics-maturity-model-guide.aspx, White Paper (2017) Big Data Maturity Assessment Tool, , https://www.infotech.com/research/ss/leverage-big-data-by-starting-small/it-big-data-maturity-assessment-tool Jacquet-Lagrèze, E., Siskos, J., Assessing a set of additive utility functions for multicriteria decision-making, the UTA method (1982) Eur J Oper Res, 10 (2), pp. 151-164 Jian, W., Xiong, R., Chiclana, F., Uninorm trust propagation and aggregation methods for group decision making in social network with four tuples information (2016) Knowl-Based Syst, 96, pp. 29-39 Keeney, R.L., Raiffa, H., (1993) Decisions with multiple objectives: preferences and value tradeoffs, , Cambridge University Press, Cambridge Kim, H.D., Lee, I., Lee, C.K., Building web 2.0 enterprises: a study of small and medium enterprises in the united states (2011) Int Small Bus J, 31 (2), pp. 156-174 Kuhrmann, M., Ternité, T., Friedrich, J., Rausch, A., Broy, M., Flexible software process lines in practice: a metamodel-based approach to effectively construct and manage families of software process models (2016) J Syst Softw, 121, pp. 49-71 Kuwata, Y., Takeda, K., Miura, H., A study on maturity model of open source software community to estimate the quality of products (2014) Proc Comput Sci, 35, pp. 1711-1717 Lian, J.-W., Ke, C.-K., Using a modified ELECTRE method for an agricultural product recommendation service on a mobile device (2016) Comput Electr Eng, 56, pp. 277-288 Lismont, J., Vanthienen, J., Baesens, B., Lemahieu, W., Defining analytics maturity indicators: a survey approach (2017) Int J Inf Manag, 37 (3), pp. 114-124 Liu, Y., Liang, C., Chiclana, F., Jian, W., A trust induced recommendation mechanism for reaching consensus in group decision making (2017) Knowl-Based Syst, 119, pp. 221-231 Marr, B., (2015) How Big Data is Changing Healthcare, Forbes, , https://www.forbes.com/sites/bernardmarr/2015/04/21/how-big-data-is-changing-healthcare/#39b365dd2873 Mousseau, V., Figueira, J.R., Naux, J.-P., Using assignment examples to infer weights for ELECTRE TRI method: some experimental results (2001) Eur J Oper Res, 130 (2), pp. 263-275 Palacio, L.H., Cálculo de los Parámetros de la Distribución de Weibull (2015) Mantenimiento En Latinoamérica, 7 (1), pp. 42-44. , http://mantenimientoenlatinoamerica.com/pdf/ML%20Volumen%207-1.pdf Perez, L.G., Mata, F., Chiclana, F., Kou, G., Herrera-Viedma, E., Modelling influence in group decision making (2016) Soft Comput, 20 (4), pp. 1653-1665 Proença, D., Borbinha, J., Maturity models for information systems a state of the art (2016) Proc Comput Sci, 100, pp. 1042-1049 Qinghua, L., Li, Z., Zhang, W., Yang, L.T., Autonomic deployment decision making for big data analytics applications in the cloud (2017) Soft Comput, 21 (16), pp. 4501-4512 Röglinger, M., Pöppelbuß, J., Becker, J., Maturity models in business process management (2012) Bus Process Manag J, 18 (2), pp. 328-346 Rouyendegh, B.D., Erol, S., Selecting the best project using the fuzzy ELECTRE method (2012) Math Prob Eng Santos, M., (2014) Las Pymes Ya Están Usando Big Data E Inteligencia De Datos, , http://www.enter.co/especiales/enterprise/big-data-tecnologia-pymes/ Schaeffer, D.M., Olson, P.C., Big data options for small and medium enterprises (2014) Rev Bus Inf Syst, 18 (1), pp. 41-46 Sevkli, M., An application of the fuzzy ELECTRE method for supplier selection (2009) Int J Prod Res, 48 (12), pp. 3393-3405 Tarhan, A., Turetken, O., Reijers, H.A., Business process maturity models: a systematic literature review (2016) Inf Softw Technol, 75, pp. 122-134 Vélez, R., (2012) Alta Gerencia: Horarios Flexibles En El Trabajo Motivan a Los Empleados Y Aumentan La Productividad von Scheel, H., von Rosing, G., Skurzak, K., Hove, M., BPM and maturity models (2015) The complete business process handbook, pp. 399-430. , Rosing M, Scheer A-W, Scheel H, (eds), Morgan Kaufmann, Burlington Zhang, H., Dong, Y., Herrera-Viedma, E., Consensus building for the heterogeneous large-scale GDM with the individual concerns and satisfactions (2018) IEEE Trans Fuzzy Syst, 26 (2), pp. 884-898 |
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Soft Computing |
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Repositorio Institucional Universidad de Medellin |
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20192020-04-29T14:53:54Z2020-04-29T14:53:54Z14327643http://hdl.handle.net/11407/575710.1007/s00500-018-3625-8Advances in technology and an increase in the amount and complexity of data that are generated in healthcare have led to an indispensable revolution in this sector related to big data. Analytics of information based on multimodal clinical data sources requires big data projects. When starting big data projects in the healthcare sector, it is often necessary to assess the maturity of an organization with respect to big data, i.e., its capacity in managing big data. The assessment of the maturity of an organization requires multicriteria decision making as there is no single criterion or dimension that defines the maturity level regarding big data but an entire set of them. Based on the ISO 15504, this article proposes a fuzzy ELECTRE structure methodology to assess the maturity level of small- and medium-sized enterprises in the healthcare sector. The obtained experimental results provide evidence that this methodology helps to determine and compare maturity levels in big data management of organizations or the evolution of maturity over time. This is also useful in terms of diagnosing the readiness of an organization before starting to implement big data initiatives or technologies. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.engSpringer VerlagIngeniería de SistemasFacultad de Ciencias Básicas;Facultad de Ingenieríashttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85057601325&doi=10.1007%2fs00500-018-3625-8&partnerID=40&md5=40b2fc2ca2a9af49f394d41372d42db223201053710550Angilella, S., Mazzu, S., The financing of innovative SMEs: a multicriteria credit rating model (2015) Eur J Oper Res, 244 (2), pp. 540-554Anún, J.P., Alarcón, R., Ranking projects of logistics platforms: a methodology based on the electre multicriteria approach (2014) Proc Soc Behav Sci, 160, pp. 5-14Bana e Costa, C.A., (1990) Readings in multiple criteria decision aid, , Springer, BerlinBenayoun, R., Roy, B., Sussmann, B., (1966) ELECTRE: Une méthode Pour Guider Le Choix En présence De Points De Vue Multiples, Note De Travail N ? 49 De La Direction Scientifique De La SEMABodas-Sagi, D.J., Labeaga Big, J.M., Data and health economics: opportunities, challenges and risks (2018) Int J Interact Multimed Artif Intell, 4 (7), pp. 47-52Bouyssou, D., Marchant, T., An axiomatic approach to noncompensatory sorting methods in MCDM, I: the case of two categories (2007) Eur J Oper Res, 178 (1), pp. 217-245Brans, J.-P., De Smet, Y., PROMETHEE methods (2016) Multiple criteria decision analysis. International series in operations research & management science, 233, pp. 187-219. , Greco S, Ehrgott M, Figueira J, (eds), Springer, New YorkCabrerizo, F.J., Al-Hmouz, R., Morfeq, A., Balamash, A.S., Martínez, M.A., Herrera-Viedma, E., Soft consensus measures in group decision making using unbalanced fuzzy linguistic information (2017) Soft Comput, 21 (11), pp. 3037-3050Camba, J.D., Contero, M., Company, P., Parametric CAD modeling: an analysis of strategies for design reusability (2016) Comput-Aided Des, 74, pp. 18-31Capuano, N., Chiclana, F., Fujita, H., Herrera-Viedma, E., Loia, V., Fuzzy group decision making with incomplete information guided by social influence (2018) IEEE Trans Fuzzy Syst, 26 (3), pp. 1704-1718Chandarana, P., Vijayalakshmi, M., Big data analytics frameworks (2014) Proceedings of the 2014 International Conference on Circuits, Systems, Communication and Information Technology Applications (CSCITA), pp. 430-434. , MumbaiDehe, B., Bamford, D., Development, test and comparison of two multiple criteria decision analysis (MCDA) models: a case of healthcare infrastructure location (2015) Exp Syst Appl, 42 (19), pp. 6717-6727Díaz-Ley, M., García, F., Piattini, M., MIS-PyME software measurement capability maturity model supporting the definition of software measurement programs and capability determination (2010) Adv Eng Softw, 41 (10-11), pp. 1223-1237Dong, Y., Li, C.-C., Chiclana, F., Herrera-Viedma, E., Average-case consistency measurement and analysis of interval-valued reciprocal preference relations (2016) Knowl-Based Syst, 114, pp. 108-117Dong, Y., Liu, W., Chiclana, F., Herrera-Viedma, E., Cabrerizo, F.J., Group decision-making based on heterogeneous preference relations with self-confidence (2017) Fuzzy Optim Decis Mak, 16 (4), pp. 429-447Eric, J.-L., An application of the UTA discriminant model for the evaluation of R & D projects (1995) Advances in multicriteria analysis. Nonconvex optimization and its applications, 5. , Pardalos PM, Siskos Y, Zopounidis C, (eds), Springer, BostonFigueira, J., Roy, B., Determining the weights of criteria in the ELECTRE type methods with a revised Simos procedure (2002) Eur J Oper Res, 139 (2), pp. 317-326Figueira, J.R., Mousseau, V., Roy, B., ELECTRE methods (2016) Multiple criteria decision analysis. International series in operations research & management science, 233, pp. 155-182. , Greco S, Ehrgott M, Figueira J, (eds), Springer, New YorkGarousi, V., Felderer, M., Hacaloglu, T., Software test maturity assessment and test process improvement: a multivocal literature review (2017) Inf Softw Technol, 85, pp. 16-42Garzás, J., Pino, F.J., Piattini, M., Fernández, C.M., A maturity model for the Spanish software industry based on ISO standards (2013) Comput Stand Interf, 35 (6), pp. 616-628Goksen, Y., Cevik, E., Avunduk, H., A case analysis on the focus on the maturity models and information technologies (2015) Proc Econ Fin, 19, pp. 208-216González-Ferrer, A., Seara, G., Cháfer, J., Mayol, J., Generating big data sets from knowledge-based decision support systems to pursue value-based healthcare (2018) Int J Interact Multimed Artif Intell, 4 (7), pp. 42-46Görög, M., A broader approach to organisational project management maturity assessment (2016) Int J Proj Manag, 34 (8), pp. 1658-1669(2017) Healthcare Smes Lead the Way with GS1 Standards, , https://www.gs1ie.org/Healthcare/Resources/Case-Studies/Healthcare-SMEs-Lead-the-Way-with-GS1-Standards.htmlHalper, F., Stoler, D., (2014) TDWI Analytics Maturity Model Guide Transforming Data with Intelligence, , https://tdwi.org/whitepapers/2014/10/tdwi-analytics-maturity-model-guide.aspx, White Paper(2017) Big Data Maturity Assessment Tool, , https://www.infotech.com/research/ss/leverage-big-data-by-starting-small/it-big-data-maturity-assessment-toolJacquet-Lagrèze, E., Siskos, J., Assessing a set of additive utility functions for multicriteria decision-making, the UTA method (1982) Eur J Oper Res, 10 (2), pp. 151-164Jian, W., Xiong, R., Chiclana, F., Uninorm trust propagation and aggregation methods for group decision making in social network with four tuples information (2016) Knowl-Based Syst, 96, pp. 29-39Keeney, R.L., Raiffa, H., (1993) Decisions with multiple objectives: preferences and value tradeoffs, , Cambridge University Press, CambridgeKim, H.D., Lee, I., Lee, C.K., Building web 2.0 enterprises: a study of small and medium enterprises in the united states (2011) Int Small Bus J, 31 (2), pp. 156-174Kuhrmann, M., Ternité, T., Friedrich, J., Rausch, A., Broy, M., Flexible software process lines in practice: a metamodel-based approach to effectively construct and manage families of software process models (2016) J Syst Softw, 121, pp. 49-71Kuwata, Y., Takeda, K., Miura, H., A study on maturity model of open source software community to estimate the quality of products (2014) Proc Comput Sci, 35, pp. 1711-1717Lian, J.-W., Ke, C.-K., Using a modified ELECTRE method for an agricultural product recommendation service on a mobile device (2016) Comput Electr Eng, 56, pp. 277-288Lismont, J., Vanthienen, J., Baesens, B., Lemahieu, W., Defining analytics maturity indicators: a survey approach (2017) Int J Inf Manag, 37 (3), pp. 114-124Liu, Y., Liang, C., Chiclana, F., Jian, W., A trust induced recommendation mechanism for reaching consensus in group decision making (2017) Knowl-Based Syst, 119, pp. 221-231Marr, B., (2015) How Big Data is Changing Healthcare, Forbes, , https://www.forbes.com/sites/bernardmarr/2015/04/21/how-big-data-is-changing-healthcare/#39b365dd2873Mousseau, V., Figueira, J.R., Naux, J.-P., Using assignment examples to infer weights for ELECTRE TRI method: some experimental results (2001) Eur J Oper Res, 130 (2), pp. 263-275Palacio, L.H., Cálculo de los Parámetros de la Distribución de Weibull (2015) Mantenimiento En Latinoamérica, 7 (1), pp. 42-44. , http://mantenimientoenlatinoamerica.com/pdf/ML%20Volumen%207-1.pdfPerez, L.G., Mata, F., Chiclana, F., Kou, G., Herrera-Viedma, E., Modelling influence in group decision making (2016) Soft Comput, 20 (4), pp. 1653-1665Proença, D., Borbinha, J., Maturity models for information systems a state of the art (2016) Proc Comput Sci, 100, pp. 1042-1049Qinghua, L., Li, Z., Zhang, W., Yang, L.T., Autonomic deployment decision making for big data analytics applications in the cloud (2017) Soft Comput, 21 (16), pp. 4501-4512Röglinger, M., Pöppelbuß, J., Becker, J., Maturity models in business process management (2012) Bus Process Manag J, 18 (2), pp. 328-346Rouyendegh, B.D., Erol, S., Selecting the best project using the fuzzy ELECTRE method (2012) Math Prob EngSantos, M., (2014) Las Pymes Ya Están Usando Big Data E Inteligencia De Datos, , http://www.enter.co/especiales/enterprise/big-data-tecnologia-pymes/Schaeffer, D.M., Olson, P.C., Big data options for small and medium enterprises (2014) Rev Bus Inf Syst, 18 (1), pp. 41-46Sevkli, M., An application of the fuzzy ELECTRE method for supplier selection (2009) Int J Prod Res, 48 (12), pp. 3393-3405Tarhan, A., Turetken, O., Reijers, H.A., Business process maturity models: a systematic literature review (2016) Inf Softw Technol, 75, pp. 122-134Vélez, R., (2012) Alta Gerencia: Horarios Flexibles En El Trabajo Motivan a Los Empleados Y Aumentan La Productividadvon Scheel, H., von Rosing, G., Skurzak, K., Hove, M., BPM and maturity models (2015) The complete business process handbook, pp. 399-430. , Rosing M, Scheer A-W, Scheel H, (eds), Morgan Kaufmann, BurlingtonZhang, H., Dong, Y., Herrera-Viedma, E., Consensus building for the heterogeneous large-scale GDM with the individual concerns and satisfactions (2018) IEEE Trans Fuzzy Syst, 26 (2), pp. 884-898Soft ComputingBig dataELECTRE methodFuzzy methodsHealthcareMaturity levelOutrankingDecision makingHealth careInformation managementClinical dataElectre methodsFuzzy methodsHealthcare sectorsMaturity levelsMulti criteria decision makingOutrankingSmall and medium sized enterpriseBig dataA fuzzy ELECTRE structure methodology to assess big data maturity in healthcare SMEsArticleinfo:eu-repo/semantics/articlehttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Peña, A., University EIA, Envigado, Colombia; Bonet, I., University EIA, Envigado, Colombia; Lochmuller, C., University EIA, Envigado, Colombia; Tabares, M.S., Universidad EAFIT, Medellín, Colombia; Piedrahita, C.C., Universidad de Medellín, Medellín, Colombia; Sánchez, C.C., Universidad de Medellín, Medellín, Colombia; Giraldo Marín, L.M., Universidad de Medellín, Medellín, Colombia; Góngora, M., Institute of Artificial Intelligence, De Montfort University, Leicester, United Kingdom; Chiclana, F., Institute of Artificial Intelligence, De Montfort University, Leicester, United Kingdom, Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spainhttp://purl.org/coar/access_right/c_16ecPeña A.Bonet I.Lochmuller C.Tabares M.S.Piedrahita C.C.Sánchez C.C.Giraldo Marín L.M.Góngora M.Chiclana F.11407/5757oai:repository.udem.edu.co:11407/57572020-05-27 16:21:08.899Repositorio Institucional Universidad de Medellinrepositorio@udem.edu.co |