{"id":{"repo_id":"middlesex","oai_identifier":"oai:repository.mdx.ac.uk:36903q"},"canonical_url":"https://search.dev.ndltd.org/etd/middlesex/oai:repository.mdx.ac.uk:36903q","repository":{"repo_id":"middlesex","name":"Middlesex University","base_url":"https://repository.mdx.ac.uk/oai2"},"display":{"title":"Auktionsmethoden für einen effizienten Einkauf: Entwicklung eines situativen Entscheidungsmodells in einer branchenübergreifenden B2B-Betrachtung","abstract":"This dissertation addresses the question of how auction designs in B2B procurement can be optimized to achieve cost efficiency under varying situational conditions. While auctions are widely recognized as a valuable instrument in strategic sourcing, the practical selection of appropriate auction configurations often remains unsystematic and driven by heuristics rather than empirical evidence. The present study aims to close this gap by developing a structured, empirically validated decision model for situational auction design. Based on a comprehensive theoretical framework, four core design dimensions were identified: auction method, auction medium, feedback parameters, and commitment. These elements were integrated into a conceptual model and empirically tested in a controlled laboratory experiment with 69 participants from the B2B sector, all experienced in procurement auctions. The experiment comprised 18 auction scenarios – nine with and nine without commitment – systematically varying method, medium, and parameter settings. The results clearly demonstrate that cost efficiency is significantly influenced by the combination of these factors. Particularly, commitment emerged as the strongest driver of efficiency, followed by the use of reverse auctions, platform-based execution, and structured feedback mechanisms. Each scenario was ranked based on average best-price outcomes, providing a robust, data-driven efficiency metric. These rankings were subsequently embedded into a situational decision model that guides practitioners in selecting the most efficient auction configuration given their specific organizational constraints. The dissertation contributes to research by bridging analytical experimentation with design-oriented model development and by introducing a behavioral perspective into auction efficiency analysis. For practice, it offers a structured and scalable decision tool that supports professionalization and standardization in auction-based procurement. The model can be operationalized as an internal sourcing guide, training framework, or digital decision assistant. It not only enhances auction outcomes but also enables a strategic, evidence-based approach to procurement design. This work thus marks a step forward in both academic auction theory and real-world procurement practice – offering a foundation for future research and practical implementation alike.","abstract_html":"This dissertation addresses the question of how auction designs in B2B procurement can be optimized to achieve cost efficiency under varying situational conditions. While auctions are widely recognized as a valuable instrument in strategic sourcing, the practical selection of appropriate auction configurations often remains unsystematic and driven by heuristics rather than empirical evidence. The present study aims to close this gap by developing a structured, empirically validated decision model for situational auction design. Based on a comprehensive theoretical framework, four core design dimensions were identified: auction method, auction medium, feedback parameters, and commitment. These elements were integrated into a conceptual model and empirically tested in a controlled laboratory experiment with 69 participants from the B2B sector, all experienced in procurement auctions. The experiment comprised 18 auction scenarios – nine with and nine without commitment – systematically varying method, medium, and parameter settings. The results clearly demonstrate that cost efficiency is significantly influenced by the combination of these factors. Particularly, commitment emerged as the strongest driver of efficiency, followed by the use of reverse auctions, platform-based execution, and structured feedback mechanisms. Each scenario was ranked based on average best-price outcomes, providing a robust, data-driven efficiency metric. These rankings were subsequently embedded into a situational decision model that guides practitioners in selecting the most efficient auction configuration given their specific organizational constraints. The dissertation contributes to research by bridging analytical experimentation with design-oriented model development and by introducing a behavioral perspective into auction efficiency analysis. For practice, it offers a structured and scalable decision tool that supports professionalization and standardization in auction-based procurement. The model can be operationalized as an internal sourcing guide, training framework, or digital decision assistant. It not only enhances auction outcomes but also enables a strategic, evidence-based approach to procurement design. This work thus marks a step forward in both academic auction theory and real-world procurement practice – offering a foundation for future research and practical implementation alike.","abstract_has_math":false,"creators":["Moseler, C.S.U."],"institution":"Middlesex University / KMU Akademie & Management AG","degree_name":"DBA","degree_level":"DBA thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2026,"date_issued":"2026","date_published":"2026","updated_at":"2026-08-21T16:46:31Z","subjects":[],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:repository.mdx.ac.uk:36903q"],"render_values":[{"text":"oai:repository.mdx.ac.uk:36903q","href":null,"code":true}]}]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"source_record":{"url":"https://repository.mdx.ac.uk/oai2?verb=GetRecord&metadataPrefix=uketd_dc&identifier=oai%3Arepository.mdx.ac.uk%3A36903q","prefix":"uketd_dc"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Moseler, C.S.U."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2026"]},{"key":"dc:date.issued","label":"Date","values":["2026"]},{"key":"dc:publisher","label":"Institution","values":["Middlesex University Research Repository"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Business School","Business and Law"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["Middlesex University / KMU Akademie & Management AG"]},{"key":"dc:relation","label":"Dc Relation","values":["https://repository.mdx.ac.uk/item/36903q"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://repository.mdx.ac.uk/item/36903q"]},{"key":"dc:type","label":"Dc Type","values":["Thesis or dissertation"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["DBA thesis"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["DBA"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:repository.mdx.ac.uk:36903q"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This dissertation addresses the question of how auction designs in B2B procurement can be optimized to achieve cost efficiency under varying situational conditions. While auctions are widely recognized as a valuable instrument in strategic sourcing, the practical selection of appropriate auction configurations often remains unsystematic and driven by heuristics rather than empirical evidence. The present study aims to close this gap by developing a structured, empirically validated decision model for situational auction design. Based on a comprehensive theoretical framework, four core design dimensions were identified: auction method, auction medium, feedback parameters, and commitment. These elements were integrated into a conceptual model and empirically tested in a controlled laboratory experiment with 69 participants from the B2B sector, all experienced in procurement auctions. The experiment comprised 18 auction scenarios – nine with and nine without commitment – systematically varying method, medium, and parameter settings. The results clearly demonstrate that cost efficiency is significantly influenced by the combination of these factors. Particularly, commitment emerged as the strongest driver of efficiency, followed by the use of reverse auctions, platform-based execution, and structured feedback mechanisms. Each scenario was ranked based on average best-price outcomes, providing a robust, data-driven efficiency metric. These rankings were subsequently embedded into a situational decision model that guides practitioners in selecting the most efficient auction configuration given their specific organizational constraints. The dissertation contributes to research by bridging analytical experimentation with design-oriented model development and by introducing a behavioral perspective into auction efficiency analysis. For practice, it offers a structured and scalable decision tool that supports professionalization and standardization in auction-based procurement. The model can be operationalized as an internal sourcing guide, training framework, or digital decision assistant. It not only enhances auction outcomes but also enables a strategic, evidence-based approach to procurement design. This work thus marks a step forward in both academic auction theory and real-world procurement practice – offering a foundation for future research and practical implementation alike."]},{"key":"dc:description.abstract","label":"Abstract","values":["This dissertation addresses the question of how auction designs in B2B procurement can be optimized to achieve cost efficiency under varying situational conditions. While auctions are widely recognized as a valuable instrument in strategic sourcing, the practical selection of appropriate auction configurations often remains unsystematic and driven by heuristics rather than empirical evidence. The present study aims to close this gap by developing a structured, empirically validated decision model for situational auction design. Based on a comprehensive theoretical framework, four core design dimensions were identified: auction method, auction medium, feedback parameters, and commitment. These elements were integrated into a conceptual model and empirically tested in a controlled laboratory experiment with 69 participants from the B2B sector, all experienced in procurement auctions. The experiment comprised 18 auction scenarios – nine with and nine without commitment – systematically varying method, medium, and parameter settings. The results clearly demonstrate that cost efficiency is significantly influenced by the combination of these factors. Particularly, commitment emerged as the strongest driver of efficiency, followed by the use of reverse auctions, platform-based execution, and structured feedback mechanisms. Each scenario was ranked based on average best-price outcomes, providing a robust, data-driven efficiency metric. These rankings were subsequently embedded into a situational decision model that guides practitioners in selecting the most efficient auction configuration given their specific organizational constraints. The dissertation contributes to research by bridging analytical experimentation with design-oriented model development and by introducing a behavioral perspective into auction efficiency analysis. For practice, it offers a structured and scalable decision tool that supports professionalization and standardization in auction-based procurement. The model can be operationalized as an internal sourcing guide, training framework, or digital decision assistant. It not only enhances auction outcomes but also enables a strategic, evidence-based approach to procurement design. This work thus marks a step forward in both academic auction theory and real-world procurement practice – offering a foundation for future research and practical implementation alike."]},{"key":"dc:title","label":"Title","values":["Auktionsmethoden für einen effizienten Einkauf: Entwicklung eines situativen Entscheidungsmodells in einer branchenübergreifenden B2B-Betrachtung"]}]}],"canonical_facts":{"dc:creator":["Moseler, C.S.U."],"dc:date":["2026"],"dc:date.issued":["2026"],"dc:description":["This dissertation addresses the question of how auction designs in B2B procurement can be optimized to achieve cost efficiency under varying situational conditions. While auctions are widely recognized as a valuable instrument in strategic sourcing, the practical selection of appropriate auction configurations often remains unsystematic and driven by heuristics rather than empirical evidence. The present study aims to close this gap by developing a structured, empirically validated decision model for situational auction design. Based on a comprehensive theoretical framework, four core design dimensions were identified: auction method, auction medium, feedback parameters, and commitment. These elements were integrated into a conceptual model and empirically tested in a controlled laboratory experiment with 69 participants from the B2B sector, all experienced in procurement auctions. The experiment comprised 18 auction scenarios – nine with and nine without commitment – systematically varying method, medium, and parameter settings. The results clearly demonstrate that cost efficiency is significantly influenced by the combination of these factors. Particularly, commitment emerged as the strongest driver of efficiency, followed by the use of reverse auctions, platform-based execution, and structured feedback mechanisms. Each scenario was ranked based on average best-price outcomes, providing a robust, data-driven efficiency metric. These rankings were subsequently embedded into a situational decision model that guides practitioners in selecting the most efficient auction configuration given their specific organizational constraints. The dissertation contributes to research by bridging analytical experimentation with design-oriented model development and by introducing a behavioral perspective into auction efficiency analysis. For practice, it offers a structured and scalable decision tool that supports professionalization and standardization in auction-based procurement. The model can be operationalized as an internal sourcing guide, training framework, or digital decision assistant. It not only enhances auction outcomes but also enables a strategic, evidence-based approach to procurement design. This work thus marks a step forward in both academic auction theory and real-world procurement practice – offering a foundation for future research and practical implementation alike."],"dc:description.abstract":["This dissertation addresses the question of how auction designs in B2B procurement can be optimized to achieve cost efficiency under varying situational conditions. While auctions are widely recognized as a valuable instrument in strategic sourcing, the practical selection of appropriate auction configurations often remains unsystematic and driven by heuristics rather than empirical evidence. The present study aims to close this gap by developing a structured, empirically validated decision model for situational auction design. Based on a comprehensive theoretical framework, four core design dimensions were identified: auction method, auction medium, feedback parameters, and commitment. These elements were integrated into a conceptual model and empirically tested in a controlled laboratory experiment with 69 participants from the B2B sector, all experienced in procurement auctions. The experiment comprised 18 auction scenarios – nine with and nine without commitment – systematically varying method, medium, and parameter settings. The results clearly demonstrate that cost efficiency is significantly influenced by the combination of these factors. Particularly, commitment emerged as the strongest driver of efficiency, followed by the use of reverse auctions, platform-based execution, and structured feedback mechanisms. Each scenario was ranked based on average best-price outcomes, providing a robust, data-driven efficiency metric. These rankings were subsequently embedded into a situational decision model that guides practitioners in selecting the most efficient auction configuration given their specific organizational constraints. The dissertation contributes to research by bridging analytical experimentation with design-oriented model development and by introducing a behavioral perspective into auction efficiency analysis. For practice, it offers a structured and scalable decision tool that supports professionalization and standardization in auction-based procurement. The model can be operationalized as an internal sourcing guide, training framework, or digital decision assistant. It not only enhances auction outcomes but also enables a strategic, evidence-based approach to procurement design. This work thus marks a step forward in both academic auction theory and real-world procurement practice – offering a foundation for future research and practical implementation alike."],"dc:identifier":["oai:repository.mdx.ac.uk:36903q"],"dc:publisher":["Middlesex University Research Repository"],"dc:publisher.department":["Business School","Business and Law"],"dc:publisher.institution":["Middlesex University / KMU Akademie & Management AG"],"dc:relation":["https://repository.mdx.ac.uk/item/36903q"],"dc:relation.isreferencedby":["https://repository.mdx.ac.uk/item/36903q"],"dc:title":["Auktionsmethoden für einen effizienten Einkauf: Entwicklung eines situativen Entscheidungsmodells in einer branchenübergreifenden B2B-Betrachtung"],"dc:type":["Thesis or dissertation"],"dc:type.qualificationlevel":["DBA thesis"],"dc:type.qualificationname":["DBA"]},"updated_at":"2026-08-21T16:46:31Z"}