RETRACTED ARTICLE: Toward a novel method to support decision-making process in health and behavioral factors analysis for the composition of IT projects teams

Information technology (IT) is a competitive advantage to organizations. To achieve this, organizations require innovative IT projects. These, in turn, require the availability and performance of qualified, ethical and healthy professionals. When selecting professionals, the organization must draw a...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Neural computing & applications 2020-08, Vol.32 (15), p.11019-11040
Hauptverfasser: Nunes, Luciano Comin, Pinheiro, Plácido Rogério, Pinheiro, Mirian Caliope Dantas, Filho, Marum Simão, Nunes, Rafael Espíndola Comin
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 11040
container_issue 15
container_start_page 11019
container_title Neural computing & applications
container_volume 32
creator Nunes, Luciano Comin
Pinheiro, Plácido Rogério
Pinheiro, Mirian Caliope Dantas
Filho, Marum Simão
Nunes, Rafael Espíndola Comin
description Information technology (IT) is a competitive advantage to organizations. To achieve this, organizations require innovative IT projects. These, in turn, require the availability and performance of qualified, ethical and healthy professionals. When selecting professionals, the organization must draw attention to technical, behavior and health factors, since these factors influence professionals’ productivity. Decision-makers need support models for professionals’ selective processes when structuring teams, including multiple criteria. This study proposes a novel decision-making support model structured in methods of “verbal decision analysis (VDA)” and “measuring attractiveness by a category-based evaluation technique (MACBETH)” to solve a conflicted dilemma, seeking to assist this process. The model was tested to analyze the desired factors in professionals’ selection process for the composition of geographically distributed teams responsible for developing and implementing IT projects. For the input values, the study used personal and professional qualitative factors, such as interpersonal skills, psychological health, physiological, cultural and intellectual indicators. When tested, the model solved the dilemma through alternatives categorization and prioritization. The test run showed inconsistency’s absence, which would not happen if the methods (VDA and MACBETH) were run individually. The model was executed successfully and had low consumption time and accurate results. Psychological and physiological factors appear to be more defining to the decision making than intellectual level and technical qualifications. Big Data mining and exploration may be a professionals’ attribute obtention way to support the model.
doi_str_mv 10.1007/s00521-018-3830-5
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_3081971201</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3081971201</sourcerecordid><originalsourceid>FETCH-LOGICAL-c1135-b9fb6a1773a9c082e0194dc2c45822640f81e839aeb50d4852a057a366e53e283</originalsourceid><addsrcrecordid>eNp1kcGK2zAQhs3SQtNtH6C3gZ7dHUmWLfcW0rQbCCwE9ywUWV47a1uuRtllX6bPWoUUeupJMPr_bwa-LPvE8AtDrO4IUXKWI1O5UAJzeZOtWCFELlCqN9kK6yL9loV4l70nOiFiUSq5yn4fts1hvWm232B9aHab_fYrNP7FhBYMzP7ZjTC52PsWogc6L4sPEVpnBxr8nE_maZgfYQneOiIYZuidGWMPZm7h6HrzPPhgRuiMjT5QGpvxlQaCzgeIvQPrp8XTEBMMfAe75sI6ORsJojMTfcjedmYk9_Hve5v9_L5tNvf5_uHHbrPe55YxIfNj3R1Lw6pKmNqi4g5ZXbSW20IqzssCO8WcErVxR4ltoSQ3KCsjytJJ4bgSt9nnKzet_3V2FPXJn0O6lrRAxeqKcWQpxa4pGzxRcJ1ewjCZ8KoZ6osGfdWgkwZ90aBl6vBrh1J2fnThH_n_pT_qjIqj</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3081971201</pqid></control><display><type>article</type><title>RETRACTED ARTICLE: Toward a novel method to support decision-making process in health and behavioral factors analysis for the composition of IT projects teams</title><source>SpringerLink Journals - AutoHoldings</source><creator>Nunes, Luciano Comin ; Pinheiro, Plácido Rogério ; Pinheiro, Mirian Caliope Dantas ; Filho, Marum Simão ; Nunes, Rafael Espíndola Comin</creator><creatorcontrib>Nunes, Luciano Comin ; Pinheiro, Plácido Rogério ; Pinheiro, Mirian Caliope Dantas ; Filho, Marum Simão ; Nunes, Rafael Espíndola Comin</creatorcontrib><description>Information technology (IT) is a competitive advantage to organizations. To achieve this, organizations require innovative IT projects. These, in turn, require the availability and performance of qualified, ethical and healthy professionals. When selecting professionals, the organization must draw attention to technical, behavior and health factors, since these factors influence professionals’ productivity. Decision-makers need support models for professionals’ selective processes when structuring teams, including multiple criteria. This study proposes a novel decision-making support model structured in methods of “verbal decision analysis (VDA)” and “measuring attractiveness by a category-based evaluation technique (MACBETH)” to solve a conflicted dilemma, seeking to assist this process. The model was tested to analyze the desired factors in professionals’ selection process for the composition of geographically distributed teams responsible for developing and implementing IT projects. For the input values, the study used personal and professional qualitative factors, such as interpersonal skills, psychological health, physiological, cultural and intellectual indicators. When tested, the model solved the dilemma through alternatives categorization and prioritization. The test run showed inconsistency’s absence, which would not happen if the methods (VDA and MACBETH) were run individually. The model was executed successfully and had low consumption time and accurate results. Psychological and physiological factors appear to be more defining to the decision making than intellectual level and technical qualifications. Big Data mining and exploration may be a professionals’ attribute obtention way to support the model.</description><identifier>ISSN: 0941-0643</identifier><identifier>EISSN: 1433-3058</identifier><identifier>DOI: 10.1007/s00521-018-3830-5</identifier><language>eng</language><publisher>London: Springer London</publisher><subject>Artificial Intelligence ; Composition ; Computational Biology/Bioinformatics ; Computational Science and Engineering ; Computer aided Medical Diagnosis ; Computer Science ; Data mining ; Data Mining and Knowledge Discovery ; Decision analysis ; Decision making ; Geographical distribution ; Image Processing and Computer Vision ; Information technology ; Multiple criterion ; Organizations ; Physiological effects ; Physiological factors ; Physiology ; Probability and Statistics in Computer Science ; Professionals ; Qualitative analysis ; Teams ; Technology assessment</subject><ispartof>Neural computing &amp; applications, 2020-08, Vol.32 (15), p.11019-11040</ispartof><rights>The Natural Computing Applications Forum 2018. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c1135-b9fb6a1773a9c082e0194dc2c45822640f81e839aeb50d4852a057a366e53e283</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00521-018-3830-5$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00521-018-3830-5$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Nunes, Luciano Comin</creatorcontrib><creatorcontrib>Pinheiro, Plácido Rogério</creatorcontrib><creatorcontrib>Pinheiro, Mirian Caliope Dantas</creatorcontrib><creatorcontrib>Filho, Marum Simão</creatorcontrib><creatorcontrib>Nunes, Rafael Espíndola Comin</creatorcontrib><title>RETRACTED ARTICLE: Toward a novel method to support decision-making process in health and behavioral factors analysis for the composition of IT projects teams</title><title>Neural computing &amp; applications</title><addtitle>Neural Comput &amp; Applic</addtitle><description>Information technology (IT) is a competitive advantage to organizations. To achieve this, organizations require innovative IT projects. These, in turn, require the availability and performance of qualified, ethical and healthy professionals. When selecting professionals, the organization must draw attention to technical, behavior and health factors, since these factors influence professionals’ productivity. Decision-makers need support models for professionals’ selective processes when structuring teams, including multiple criteria. This study proposes a novel decision-making support model structured in methods of “verbal decision analysis (VDA)” and “measuring attractiveness by a category-based evaluation technique (MACBETH)” to solve a conflicted dilemma, seeking to assist this process. The model was tested to analyze the desired factors in professionals’ selection process for the composition of geographically distributed teams responsible for developing and implementing IT projects. For the input values, the study used personal and professional qualitative factors, such as interpersonal skills, psychological health, physiological, cultural and intellectual indicators. When tested, the model solved the dilemma through alternatives categorization and prioritization. The test run showed inconsistency’s absence, which would not happen if the methods (VDA and MACBETH) were run individually. The model was executed successfully and had low consumption time and accurate results. Psychological and physiological factors appear to be more defining to the decision making than intellectual level and technical qualifications. Big Data mining and exploration may be a professionals’ attribute obtention way to support the model.</description><subject>Artificial Intelligence</subject><subject>Composition</subject><subject>Computational Biology/Bioinformatics</subject><subject>Computational Science and Engineering</subject><subject>Computer aided Medical Diagnosis</subject><subject>Computer Science</subject><subject>Data mining</subject><subject>Data Mining and Knowledge Discovery</subject><subject>Decision analysis</subject><subject>Decision making</subject><subject>Geographical distribution</subject><subject>Image Processing and Computer Vision</subject><subject>Information technology</subject><subject>Multiple criterion</subject><subject>Organizations</subject><subject>Physiological effects</subject><subject>Physiological factors</subject><subject>Physiology</subject><subject>Probability and Statistics in Computer Science</subject><subject>Professionals</subject><subject>Qualitative analysis</subject><subject>Teams</subject><subject>Technology assessment</subject><issn>0941-0643</issn><issn>1433-3058</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp1kcGK2zAQhs3SQtNtH6C3gZ7dHUmWLfcW0rQbCCwE9ywUWV47a1uuRtllX6bPWoUUeupJMPr_bwa-LPvE8AtDrO4IUXKWI1O5UAJzeZOtWCFELlCqN9kK6yL9loV4l70nOiFiUSq5yn4fts1hvWm232B9aHab_fYrNP7FhBYMzP7ZjTC52PsWogc6L4sPEVpnBxr8nE_maZgfYQneOiIYZuidGWMPZm7h6HrzPPhgRuiMjT5QGpvxlQaCzgeIvQPrp8XTEBMMfAe75sI6ORsJojMTfcjedmYk9_Hve5v9_L5tNvf5_uHHbrPe55YxIfNj3R1Lw6pKmNqi4g5ZXbSW20IqzssCO8WcErVxR4ltoSQ3KCsjytJJ4bgSt9nnKzet_3V2FPXJn0O6lrRAxeqKcWQpxa4pGzxRcJ1ewjCZ8KoZ6osGfdWgkwZ90aBl6vBrh1J2fnThH_n_pT_qjIqj</recordid><startdate>20200801</startdate><enddate>20200801</enddate><creator>Nunes, Luciano Comin</creator><creator>Pinheiro, Plácido Rogério</creator><creator>Pinheiro, Mirian Caliope Dantas</creator><creator>Filho, Marum Simão</creator><creator>Nunes, Rafael Espíndola Comin</creator><general>Springer London</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20200801</creationdate><title>RETRACTED ARTICLE: Toward a novel method to support decision-making process in health and behavioral factors analysis for the composition of IT projects teams</title><author>Nunes, Luciano Comin ; Pinheiro, Plácido Rogério ; Pinheiro, Mirian Caliope Dantas ; Filho, Marum Simão ; Nunes, Rafael Espíndola Comin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1135-b9fb6a1773a9c082e0194dc2c45822640f81e839aeb50d4852a057a366e53e283</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Artificial Intelligence</topic><topic>Composition</topic><topic>Computational Biology/Bioinformatics</topic><topic>Computational Science and Engineering</topic><topic>Computer aided Medical Diagnosis</topic><topic>Computer Science</topic><topic>Data mining</topic><topic>Data Mining and Knowledge Discovery</topic><topic>Decision analysis</topic><topic>Decision making</topic><topic>Geographical distribution</topic><topic>Image Processing and Computer Vision</topic><topic>Information technology</topic><topic>Multiple criterion</topic><topic>Organizations</topic><topic>Physiological effects</topic><topic>Physiological factors</topic><topic>Physiology</topic><topic>Probability and Statistics in Computer Science</topic><topic>Professionals</topic><topic>Qualitative analysis</topic><topic>Teams</topic><topic>Technology assessment</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nunes, Luciano Comin</creatorcontrib><creatorcontrib>Pinheiro, Plácido Rogério</creatorcontrib><creatorcontrib>Pinheiro, Mirian Caliope Dantas</creatorcontrib><creatorcontrib>Filho, Marum Simão</creatorcontrib><creatorcontrib>Nunes, Rafael Espíndola Comin</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Neural computing &amp; applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nunes, Luciano Comin</au><au>Pinheiro, Plácido Rogério</au><au>Pinheiro, Mirian Caliope Dantas</au><au>Filho, Marum Simão</au><au>Nunes, Rafael Espíndola Comin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>RETRACTED ARTICLE: Toward a novel method to support decision-making process in health and behavioral factors analysis for the composition of IT projects teams</atitle><jtitle>Neural computing &amp; applications</jtitle><stitle>Neural Comput &amp; Applic</stitle><date>2020-08-01</date><risdate>2020</risdate><volume>32</volume><issue>15</issue><spage>11019</spage><epage>11040</epage><pages>11019-11040</pages><issn>0941-0643</issn><eissn>1433-3058</eissn><abstract>Information technology (IT) is a competitive advantage to organizations. To achieve this, organizations require innovative IT projects. These, in turn, require the availability and performance of qualified, ethical and healthy professionals. When selecting professionals, the organization must draw attention to technical, behavior and health factors, since these factors influence professionals’ productivity. Decision-makers need support models for professionals’ selective processes when structuring teams, including multiple criteria. This study proposes a novel decision-making support model structured in methods of “verbal decision analysis (VDA)” and “measuring attractiveness by a category-based evaluation technique (MACBETH)” to solve a conflicted dilemma, seeking to assist this process. The model was tested to analyze the desired factors in professionals’ selection process for the composition of geographically distributed teams responsible for developing and implementing IT projects. For the input values, the study used personal and professional qualitative factors, such as interpersonal skills, psychological health, physiological, cultural and intellectual indicators. When tested, the model solved the dilemma through alternatives categorization and prioritization. The test run showed inconsistency’s absence, which would not happen if the methods (VDA and MACBETH) were run individually. The model was executed successfully and had low consumption time and accurate results. Psychological and physiological factors appear to be more defining to the decision making than intellectual level and technical qualifications. Big Data mining and exploration may be a professionals’ attribute obtention way to support the model.</abstract><cop>London</cop><pub>Springer London</pub><doi>10.1007/s00521-018-3830-5</doi><tpages>22</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0941-0643
ispartof Neural computing & applications, 2020-08, Vol.32 (15), p.11019-11040
issn 0941-0643
1433-3058
language eng
recordid cdi_proquest_journals_3081971201
source SpringerLink Journals - AutoHoldings
subjects Artificial Intelligence
Composition
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer aided Medical Diagnosis
Computer Science
Data mining
Data Mining and Knowledge Discovery
Decision analysis
Decision making
Geographical distribution
Image Processing and Computer Vision
Information technology
Multiple criterion
Organizations
Physiological effects
Physiological factors
Physiology
Probability and Statistics in Computer Science
Professionals
Qualitative analysis
Teams
Technology assessment
title RETRACTED ARTICLE: Toward a novel method to support decision-making process in health and behavioral factors analysis for the composition of IT projects teams
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T14%3A29%3A28IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=RETRACTED%20ARTICLE:%20Toward%20a%20novel%20method%20to%20support%20decision-making%20process%20in%20health%20and%20behavioral%20factors%20analysis%20for%20the%20composition%20of%20IT%20projects%20teams&rft.jtitle=Neural%20computing%20&%20applications&rft.au=Nunes,%20Luciano%20Comin&rft.date=2020-08-01&rft.volume=32&rft.issue=15&rft.spage=11019&rft.epage=11040&rft.pages=11019-11040&rft.issn=0941-0643&rft.eissn=1433-3058&rft_id=info:doi/10.1007/s00521-018-3830-5&rft_dat=%3Cproquest_cross%3E3081971201%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3081971201&rft_id=info:pmid/&rfr_iscdi=true