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    <id>8237</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
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    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>19</issue>
    <volume>12</volume>
    <type>article</type>
    <publisherName>MDPI</publisherName>
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    <title language="eng">Towards Sustainable Cities: Utilizing Floating Car Data to Support Location-Based Road Network Performance Measurements</title>
    <abstract language="eng">Road network performance (RNP) is a key element for urban sustainability as it has a significant impact on economy, environment, and society. Poor RNP can lead to traffic congestion, which can lead to higher transportation costs, more pollution and health issues regarding the urban population. To evaluate the effects of the RNP, the involved stakeholders need a real-world data base to work with. This paper develops a data collection approach to enable location-based RNP analysis using publicly available traffic information. Therefore, we use reachable range requests implemented by navigation service providers to retrieve travel times, travel speeds, and traffic conditions. To demonstrate the practicability of the proposed methodology, a comparison of four German cities is made, considering the network characteristics with respect to detours, infrastructure, and traffic congestion. The results are combined with cost rates to compare the economical dimension of sustainability of the chosen cities. Our results show that digitization eases the assessment of traffic data and that a combination of several indicators must be considered depending on the relevant sustainability dimension decisions are made from.</abstract>
    <parentTitle language="eng">Sustainability</parentTitle>
    <identifier type="doi">10.3390/su12198145</identifier>
    <enrichment key="opus.import.date">2025-06-04T20:26:41+00:00</enrichment>
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    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Maximilian Braun</author>
    <author>Jan Kunkler</author>
    <author>Florian Kellner</author>
    <collection role="institutes" number="FakBW">Fakultät Business and Management</collection>
    <collection role="othpublikationsherkunft" number="">Externe Publikationen</collection>
    <collection role="oaweg" number="">Gold Open Access- Erstveröffentlichung in einem/als Open-Access-Medium</collection>
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    <collection role="persons" number="kellnerfbm">Kellner, Florian (Prof. Dr.) - FBM</collection>
  </doc>
  <doc>
    <id>8280</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>95</pageFirst>
    <pageLast>98</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bookpart</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace>Piscataway, NJ</publisherPlace>
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    <title language="eng">Optimal engine technology mix in a low carbon economy</title>
    <abstract language="eng">Environmental regulations force automotive companies to modify the powertrain technology portfolio offered to the customer to comply with greenhouse gas (GHG) emission targets. Automotive companies, in turn, are faced with the decision of finding the right powertrain technology portfolio because the selection of a particular technology portfolio affects different company targets at the same time. What makes this decision even more interesting is the fact that future market shares of the different technologies are uncertain. With its numerous objectives, this challenge requires multi-criteria decision-making techniques to identify the optimal powertrain technology portfolio. The objective of this research is to present a new decision support approach for assembling optimal powertrain technology portfolios while making decision-makers aware of the trade-offs between the achievable market share, the market share risk, and the GHG emissions generated by the selected vehicle fleet. The proposed approach combines `a posteriori' decision-making, multi-objective optimization, and the Markowitz portfolio theory. In an application case, the outlooks of selected market studies are fed into the proposed decision support system. The result is a visualization and analysis of the current real-world decision-making problem faced by many automotive companies. Interesting findings of this research include that for the assumed GHG restrictions in place in 2030, there exists no optimal powertrain technology portfolio that is not composed of at least 20% of electric vehicles.</abstract>
    <parentTitle language="eng">2020 International Conference on Decision Aid Sciences and Application (DASA), 08-09 November 2020, Sakheer, Bahrain</parentTitle>
    <identifier type="isbn">978-1-7281-9677-0</identifier>
    <identifier type="doi">10.1109/DASA51403.2020.9317094</identifier>
    <enrichment key="opus.import.date">2025-06-05T12:03:33+00:00</enrichment>
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    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Florian Kellner</author>
    <author>Bernhard Lienland</author>
    <author>Sebastian Utz</author>
    <collection role="institutes" number="FakBW">Fakultät Business and Management</collection>
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    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
    <collection role="persons" number="kellnerfbm">Kellner, Florian (Prof. Dr.) - FBM</collection>
    <collection role="persons" number="lienlandfbm">Lienland, Bernhard (Prof. Dr.) - FBM</collection>
  </doc>
  <doc>
    <id>8225</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
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    <type>preprint</type>
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    <title language="eng">Generating Greenhouse Gas Cutting Incentives when Allocating Carbon Dioxide Emissions to Shipments in Road Freight Transportation</title>
    <abstract language="eng">Road freight transportation accounts for a great share of the anthropogenic greenhouse gas (GHG) emissions. In order to provide a common methodology for carbon accounting related to transport activities, the European Committee for Standardization has published the European Norm EN-16258. Unfortunately, EN-16258 contains in its current version some gaps and ambiguities and leaves room for interpretation, which makes the comparison of the environmental performance of different logistics networks still difficult and hinders the identification of best practices. This research aims to overcome the ambiguities of EN-16258 concerning the allocation of GHG emissions to shipments in road freight transportation. In detail, we apply concepts of the cooperative game theory to identify among all allocation units specified by EN-16258 the most meaningful one. In doing so, we continue previous research projects that analyzed two important aspects of the EN-16258 allocation rules: accuracy and fairness. This study provides further insights into this allocation problem by investigating the incentive power of the different allocation schemes to opt for the GHG minimal way of running a road freight transport network. First, we complement the list of transport scenarios introduced by the prior research projects and present two novel transport scenarios. Second, we carry out a series of numerical experiments to compare the performance of the EN-16258 allocation rules with respect to accuracy, fairness, and the GHG minimizing incentive. Across all aspects, and taking the findings of the prior research projects into account, we conclude that the distance-based allocation rule is the most meaningful one.</abstract>
    <parentTitle language="eng">SSRN Electronic Journal</parentTitle>
    <identifier type="doi">10.2139/ssrn.3518014</identifier>
    <note>Erschienen bei Springer im OR-Spektrum 44, 2020(3): https://doi.org/10.1007/s00291-022-00675-y</note>
    <enrichment key="opus.import.date">2025-06-04T20:26:41+00:00</enrichment>
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    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Florian Kellner</author>
    <collection role="institutes" number="FakBW">Fakultät Business and Management</collection>
    <collection role="othpublikationsherkunft" number="">Externe Publikationen</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
    <collection role="persons" number="kellnerfbm">Kellner, Florian (Prof. Dr.) - FBM</collection>
  </doc>
  <doc>
    <id>8289</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>XVIII, 283</pageNumber>
    <edition>2., überarbeitete und erweiterte Auflage</edition>
    <issue/>
    <volume/>
    <type>book</type>
    <publisherName>Springer Gabler</publisherName>
    <publisherPlace>Berlin</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
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    <title language="deu">Übungsbuch Produktionswirtschaft : Planung, Steuerung und Industrie 4.0</title>
    <abstract language="deu">Dieses Buch bietet Studierenden mehr als 70 Übungsaufgaben und drei Fallstudien inklusive ausführlicher Lösungen zu ausgewählten Themen der Produktionswirtschaft und Industrie 4.0. Jedes Kapitel enthält eine kurze Einleitung sowie zu erreichende Lernziele. Querverweise auf das Lehrbuch „Produktionswirtschaft“ von Kellner/Lienland/Lukesch erleichtern das Selbststudium und ermöglichen eine optimale Prüfungsvorbereitung. In der 2. Auflage wurden umfangreiche Überarbeitungen hinsichtlich Sprache und Aufbau von Aufgaben, Lösungswegen und Abbildungen vorgenommen sowie zahlreiche neue Aufgaben ergänzt.</abstract>
    <identifier type="isbn">978-3-662-62086-1</identifier>
    <identifier type="doi">10.1007/978-3-662-62087-8</identifier>
    <enrichment key="opus.import.date">2025-06-05T12:03:33+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Maximilian Lukesch</author>
    <author>Florian Kellner</author>
    <collection role="institutes" number="FakBW">Fakultät Business and Management</collection>
    <collection role="othpublikationsherkunft" number="">Externe Publikationen</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
    <collection role="persons" number="kellnerfbm">Kellner, Florian (Prof. Dr.) - FBM</collection>
  </doc>
  <doc>
    <id>6387</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>XXI, 399</pageNumber>
    <edition>2., aktualisierte und erweiterte Auflage</edition>
    <issue/>
    <volume/>
    <type>book</type>
    <publisherName>Springer Gabler</publisherName>
    <publisherPlace>Heidelberg</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
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    <title language="deu">Produktionswirtschaft : Planung, Steuerung und Industrie 4.0</title>
    <abstract language="deu">Dieses Buch gibt einen umfassenden Überblick über wichtige Bereiche der Produktionswirtschaft. Der Schwerpunkt liegt auf dem operativen Produktionsmanagement. Es zeigt den Einsatz der Produktionsfaktoren Mensch, Betriebsmittel und Material, erklärt die Bedeutung von Informationen für die betriebliche Führung und bietet anhand zahlreicher Beispiele einen breiten Einblick in die Planung und Steuerung industrieller Produktion. Ausführlich werden neben produktionswirtschaftlichen Grundlagen der Ablauf und Inhalt von Planungs- und Steuerungsprozessen erläutert. Auch das aktuelle Thema Industrie 4.0 sowie cyber-physische Systeme werden dargestellt. &#13;
&#13;
In der 2. Auflage wurden umfangreiche Überarbeitungen hinsichtlich Sprache und Aufbau vorgenommen sowie anschauliche Beispielaufgaben, neue Unternehmensbeispiele und hilfreiche Hintergrunderklärungen ergänzt.</abstract>
    <identifier type="doi">10.1007/978-3-662-61446-4</identifier>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Florian Kellner</author>
    <author>Bernhard Lienland</author>
    <author>Maximilian Lukesch</author>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Produktion</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Leistungserstellung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Operatives Management</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Industrie 4.0</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Produktionsmanagement</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Produktionsfaktoren</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Produktionsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Produktionssteuerung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Kapazitätsbedarfsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Materialbedarfsplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Losgrößenplanung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Auftragsterminierung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Industrielle Produktion</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>cyber-physische Systeme</value>
    </subject>
    <collection role="institutes" number="FakBW">Fakultät Business and Management</collection>
    <collection role="othpublikationsherkunft" number="">Externe Publikationen</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
    <collection role="persons" number="kellnerfbm">Kellner, Florian (Prof. Dr.) - FBM</collection>
    <collection role="persons" number="lienlandfbm">Lienland, Bernhard (Prof. Dr.) - FBM</collection>
  </doc>
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