Green logistics – measures for reducing CO2
Paper presents measures for reducing CO2 in logistic operations, especially transportation. Fundamental measures (transport fuels, improving vehicle efficiency, vehicle technology, transport efficiency, traffic infrastructure management, integration of transport systems, safety and security, economi...
Gespeichert in:
Veröffentlicht in: | Pomorstvo 2015-06, Vol.29 (1), p.45 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | 1 |
container_start_page | 45 |
container_title | Pomorstvo |
container_volume | 29 |
creator | Antoni, Alfonz Perić, Mile Čišić, Dragan |
description | Paper presents measures for reducing CO2 in logistic operations, especially transportation. Fundamental measures (transport fuels, improving vehicle efficiency, vehicle technology, transport efficiency, traffic infrastructure management, integration of transport systems, safety and security, economic aspects of change, broader environmental impacts, equity and accessibility, information and awareness, infrastructure, pricing and taxation and regulation) have been recognized, and discussed. Data obtained using questionnaires on substantial number of experts has been used and statistically processed. Using data mining techniques, authors have isolated information from a data set and converted it into a comprehensible structure for additional utilisation. Correlation analysis, multilevel hierarchy and principal factor analysis have been used. Finally, Bayesian classifier method is used to define Bayesian network in order to show interconnections between chosen factors. |
format | Article |
fullrecord | <record><control><sourceid>hrcak</sourceid><recordid>TN_cdi_hrcak_primary_oai_hrcak_srce_hr_140206</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>oai_hrcak_srce_hr_140206</sourcerecordid><originalsourceid>FETCH-hrcak_primary_oai_hrcak_srce_hr_1402063</originalsourceid><addsrcrecordid>eNpjYuA0tDAx07UwMbZgAbKNjY10DcwNLTgYeIuLM5MMjMwszQ3NjEw4GXTdi1JT8xRy8tMzi0syk4sVHjVMVshNTSwuLUotVkjLL1IoSk0pTc7MS1dw9jfiYWBNS8wpTuWF0twMum6uIc4euhlFyYnZ8QVFmbmJRZXx-YmZ8RCR4qLkVCAz3tDEwMjAzJhU9QAouj12</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Green logistics – measures for reducing CO2</title><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Antoni, Alfonz ; Perić, Mile ; Čišić, Dragan</creator><creatorcontrib>Antoni, Alfonz ; Perić, Mile ; Čišić, Dragan</creatorcontrib><description>Paper presents measures for reducing CO2 in logistic operations, especially transportation. Fundamental measures (transport fuels, improving vehicle efficiency, vehicle technology, transport efficiency, traffic infrastructure management, integration of transport systems, safety and security, economic aspects of change, broader environmental impacts, equity and accessibility, information and awareness, infrastructure, pricing and taxation and regulation) have been recognized, and discussed. Data obtained using questionnaires on substantial number of experts has been used and statistically processed. Using data mining techniques, authors have isolated information from a data set and converted it into a comprehensible structure for additional utilisation. Correlation analysis, multilevel hierarchy and principal factor analysis have been used. Finally, Bayesian classifier method is used to define Bayesian network in order to show interconnections between chosen factors.</description><identifier>ISSN: 1332-0718</identifier><identifier>EISSN: 1846-8438</identifier><language>eng</language><publisher>Pomorski fakultet u Rijeci</publisher><subject>Green logistics ; Logistic environmental impact ; Measures reducing CO2</subject><ispartof>Pomorstvo, 2015-06, Vol.29 (1), p.45</ispartof><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0001-6235-0987</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,780,784,885</link.rule.ids></links><search><creatorcontrib>Antoni, Alfonz</creatorcontrib><creatorcontrib>Perić, Mile</creatorcontrib><creatorcontrib>Čišić, Dragan</creatorcontrib><title>Green logistics – measures for reducing CO2</title><title>Pomorstvo</title><description>Paper presents measures for reducing CO2 in logistic operations, especially transportation. Fundamental measures (transport fuels, improving vehicle efficiency, vehicle technology, transport efficiency, traffic infrastructure management, integration of transport systems, safety and security, economic aspects of change, broader environmental impacts, equity and accessibility, information and awareness, infrastructure, pricing and taxation and regulation) have been recognized, and discussed. Data obtained using questionnaires on substantial number of experts has been used and statistically processed. Using data mining techniques, authors have isolated information from a data set and converted it into a comprehensible structure for additional utilisation. Correlation analysis, multilevel hierarchy and principal factor analysis have been used. Finally, Bayesian classifier method is used to define Bayesian network in order to show interconnections between chosen factors.</description><subject>Green logistics</subject><subject>Logistic environmental impact</subject><subject>Measures reducing CO2</subject><issn>1332-0718</issn><issn>1846-8438</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNpjYuA0tDAx07UwMbZgAbKNjY10DcwNLTgYeIuLM5MMjMwszQ3NjEw4GXTdi1JT8xRy8tMzi0syk4sVHjVMVshNTSwuLUotVkjLL1IoSk0pTc7MS1dw9jfiYWBNS8wpTuWF0twMum6uIc4euhlFyYnZ8QVFmbmJRZXx-YmZ8RCR4qLkVCAz3tDEwMjAzJhU9QAouj12</recordid><startdate>20150630</startdate><enddate>20150630</enddate><creator>Antoni, Alfonz</creator><creator>Perić, Mile</creator><creator>Čišić, Dragan</creator><general>Pomorski fakultet u Rijeci</general><scope>VP8</scope><orcidid>https://orcid.org/0000-0001-6235-0987</orcidid></search><sort><creationdate>20150630</creationdate><title>Green logistics – measures for reducing CO2</title><author>Antoni, Alfonz ; Perić, Mile ; Čišić, Dragan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-hrcak_primary_oai_hrcak_srce_hr_1402063</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Green logistics</topic><topic>Logistic environmental impact</topic><topic>Measures reducing CO2</topic><toplevel>online_resources</toplevel><creatorcontrib>Antoni, Alfonz</creatorcontrib><creatorcontrib>Perić, Mile</creatorcontrib><creatorcontrib>Čišić, Dragan</creatorcontrib><collection>Hrcak: Portal of scientific journals of Croatia</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Antoni, Alfonz</au><au>Perić, Mile</au><au>Čišić, Dragan</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Green logistics – measures for reducing CO2</atitle><jtitle>Pomorstvo</jtitle><date>2015-06-30</date><risdate>2015</risdate><volume>29</volume><issue>1</issue><spage>45</spage><pages>45-</pages><issn>1332-0718</issn><eissn>1846-8438</eissn><abstract>Paper presents measures for reducing CO2 in logistic operations, especially transportation. Fundamental measures (transport fuels, improving vehicle efficiency, vehicle technology, transport efficiency, traffic infrastructure management, integration of transport systems, safety and security, economic aspects of change, broader environmental impacts, equity and accessibility, information and awareness, infrastructure, pricing and taxation and regulation) have been recognized, and discussed. Data obtained using questionnaires on substantial number of experts has been used and statistically processed. Using data mining techniques, authors have isolated information from a data set and converted it into a comprehensible structure for additional utilisation. Correlation analysis, multilevel hierarchy and principal factor analysis have been used. Finally, Bayesian classifier method is used to define Bayesian network in order to show interconnections between chosen factors.</abstract><pub>Pomorski fakultet u Rijeci</pub><orcidid>https://orcid.org/0000-0001-6235-0987</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1332-0718 |
ispartof | Pomorstvo, 2015-06, Vol.29 (1), p.45 |
issn | 1332-0718 1846-8438 |
language | eng |
recordid | cdi_hrcak_primary_oai_hrcak_srce_hr_140206 |
source | DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
subjects | Green logistics Logistic environmental impact Measures reducing CO2 |
title | Green logistics – measures for reducing CO2 |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-11T06%3A42%3A55IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-hrcak&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Green%20logistics%20%E2%80%93%20measures%20for%20reducing%20CO2&rft.jtitle=Pomorstvo&rft.au=Antoni,%20Alfonz&rft.date=2015-06-30&rft.volume=29&rft.issue=1&rft.spage=45&rft.pages=45-&rft.issn=1332-0718&rft.eissn=1846-8438&rft_id=info:doi/&rft_dat=%3Chrcak%3Eoai_hrcak_srce_hr_140206%3C/hrcak%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |