Podejście rozmyte w prototypowaniu strategii konkurencyjności MŚP
Supporting the decision-making in unstructured problems, such as tasks related to developing a competitiveness strategy, is difficult and inefficient without access to expert knowledge. However, not all companies, for example SMEs, have the ability to use their resources. There is a need to replace...
Ausführliche Beschreibung
Autor*in: |
Katarzyna Rostek [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch ; Polnisch |
Erschienen: |
2015 |
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Schlagwörter: |
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Übergeordnetes Werk: |
In: Problemy Zarządzania - Wydawnictwo Naukowe Wydziału Zarządzania Uniwersytetu Warszawskiego, 2019, 13(2015), 2(52) t.1, Seite 162-175 |
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Übergeordnetes Werk: |
volume:13 ; year:2015 ; number:2(52) t.1 ; pages:162-175 |
Links: |
Link aufrufen |
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DOI / URN: |
DOI:10.7172/1644-9584.52.13 |
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Katalog-ID: |
DOAJ032066422 |
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DOI:10.7172/1644-9584.52.13 doi (DE-627)DOAJ032066422 (DE-599)DOAJffb6c2fe6a40422aaecf53d2b299f6d3 DE-627 ger DE-627 rakwb eng pol HD28-70 HG1-9999 Katarzyna Rostek verfasserin aut Podejście rozmyte w prototypowaniu strategii konkurencyjności MŚP 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Supporting the decision-making in unstructured problems, such as tasks related to developing a competitiveness strategy, is difficult and inefficient without access to expert knowledge. However, not all companies, for example SMEs, have the ability to use their resources. There is a need to replace the experience and skills of experts by knowledge obtained through the analysis of data from the company and its environment. This data is usually incomplete and inaccurate, which affects the precision of decisions made. The methods of developing competitiveness strategies that are known from literature do not use available data mining techniques or fuzzy inference techniques taking into account the uncertainty of data. The proposed method, which integrates the above techniques, is an attractive alternative to the use of qualitative or qualitative-quantitative methods. The verification of the method was carried out on a group of SMEs providing medical services. competitiveness strategy competitive analysis uncertain and imprecise data hybrid ahp regression analysis fuzzy decision trees Management. Industrial management Finance In Problemy Zarządzania Wydawnictwo Naukowe Wydziału Zarządzania Uniwersytetu Warszawskiego, 2019 13(2015), 2(52) t.1, Seite 162-175 (DE-627)734735685 (DE-600)2698189-0 23008792 nnns volume:13 year:2015 number:2(52) t.1 pages:162-175 https://doi.org/DOI:10.7172/1644-9584.52.13 kostenfrei https://doaj.org/article/ffb6c2fe6a40422aaecf53d2b299f6d3 kostenfrei https://pz.wz.uw.edu.pl/resources/html/article/details?id=169604 kostenfrei https://doaj.org/toc/1644-9584 Journal toc kostenfrei https://doaj.org/toc/2300-8792 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2015 2(52) t.1 162-175 |
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Supporting the decision-making in unstructured problems, such as tasks related to developing a competitiveness strategy, is difficult and inefficient without access to expert knowledge. However, not all companies, for example SMEs, have the ability to use their resources. There is a need to replace the experience and skills of experts by knowledge obtained through the analysis of data from the company and its environment. This data is usually incomplete and inaccurate, which affects the precision of decisions made. The methods of developing competitiveness strategies that are known from literature do not use available data mining techniques or fuzzy inference techniques taking into account the uncertainty of data. The proposed method, which integrates the above techniques, is an attractive alternative to the use of qualitative or qualitative-quantitative methods. The verification of the method was carried out on a group of SMEs providing medical services. |
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Supporting the decision-making in unstructured problems, such as tasks related to developing a competitiveness strategy, is difficult and inefficient without access to expert knowledge. However, not all companies, for example SMEs, have the ability to use their resources. There is a need to replace the experience and skills of experts by knowledge obtained through the analysis of data from the company and its environment. This data is usually incomplete and inaccurate, which affects the precision of decisions made. The methods of developing competitiveness strategies that are known from literature do not use available data mining techniques or fuzzy inference techniques taking into account the uncertainty of data. The proposed method, which integrates the above techniques, is an attractive alternative to the use of qualitative or qualitative-quantitative methods. The verification of the method was carried out on a group of SMEs providing medical services. |
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Supporting the decision-making in unstructured problems, such as tasks related to developing a competitiveness strategy, is difficult and inefficient without access to expert knowledge. However, not all companies, for example SMEs, have the ability to use their resources. There is a need to replace the experience and skills of experts by knowledge obtained through the analysis of data from the company and its environment. This data is usually incomplete and inaccurate, which affects the precision of decisions made. The methods of developing competitiveness strategies that are known from literature do not use available data mining techniques or fuzzy inference techniques taking into account the uncertainty of data. The proposed method, which integrates the above techniques, is an attractive alternative to the use of qualitative or qualitative-quantitative methods. The verification of the method was carried out on a group of SMEs providing medical services. |
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