{"id":{"repo_id":"rgu","oai_identifier":"oai:rgu-repository.worktribe.com:3085475"},"canonical_url":"https://search.dev.ndltd.org/etd/rgu/oai:rgu-repository.worktribe.com:3085475","repository":{"repo_id":"rgu","name":"Robert Gordon University","base_url":"https://rgu-repository.worktribe.com/oaiprovider"},"display":{"title":"Scheduling techniques that accommodate complexity: industrial practices and new approaches.","abstract":"Complexity is a recognized factor that impacts project performance, yet quantifying this impact remains elusive. The Newtonian certainty of breaking down a project's schedule through a work breakdown structure into discrete activities fails to acknowledge the interwoven nature, iterative behaviour, and emergent state that arises when dealing with complexity. To understand the impact of complexity on a project's schedule, it is essential to identify, assign, and quantify complexity traits relative to the project's network. Through the research supporting the thesis, a comprehensive literature search has identified a set of complexity traits, and further research has isolated discrete complexity strings within project schedule networks. Assigning these complexity traits to these strings unveils the DNA of complexity within any given project schedule. A two-stage Delphi Method is employed to allocate the identified complexity traits to the discrete complexity strings. The two stages involve initially assigning traits to specific strings and subsequently recognizing the complexity strings with the most profound impact. A Forced Ranking Scale is then utilised to assess the effects of these complexity traits on the identified complexity strings. This method facilitates the determination of the impact of any set of traits on a specific complexity string, ultimately leading to the calculation of a revised makespan. The resulting affected schedule vividly demonstrates the discrete consequences of these traits within the determined complexity strings while also aiding in identifying activities directly and indirectly affected by the traits. The thesis offers methods for identifying and associating complexity strings with distinct complexity traits. Furthermore, it outlines a procedure for calculating and substantiating the influence of these complexity traits on a project's schedule makespan.","abstract_html":"Complexity is a recognized factor that impacts project performance, yet quantifying this impact remains elusive. The Newtonian certainty of breaking down a project's schedule through a work breakdown structure into discrete activities fails to acknowledge the interwoven nature, iterative behaviour, and emergent state that arises when dealing with complexity. To understand the impact of complexity on a project's schedule, it is essential to identify, assign, and quantify complexity traits relative to the project's network. Through the research supporting the thesis, a comprehensive literature search has identified a set of complexity traits, and further research has isolated discrete complexity strings within project schedule networks. Assigning these complexity traits to these strings unveils the DNA of complexity within any given project schedule. A two-stage Delphi Method is employed to allocate the identified complexity traits to the discrete complexity strings. The two stages involve initially assigning traits to specific strings and subsequently recognizing the complexity strings with the most profound impact. A Forced Ranking Scale is then utilised to assess the effects of these complexity traits on the identified complexity strings. This method facilitates the determination of the impact of any set of traits on a specific complexity string, ultimately leading to the calculation of a revised makespan. The resulting affected schedule vividly demonstrates the discrete consequences of these traits within the determined complexity strings while also aiding in identifying activities directly and indirectly affected by the traits. The thesis offers methods for identifying and associating complexity strings with distinct complexity traits. Furthermore, it outlines a procedure for calculating and substantiating the influence of these complexity traits on a project's schedule makespan.","abstract_has_math":false,"creators":["Lambert, Jeremy Clifford"],"institution":"Robert Gordon University","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Q.M.M. Zaman, R. Laing, D. Ahiaga-Dagbui and P. 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The two stages involve initially assigning traits to specific strings and subsequently recognizing the complexity strings with the most profound impact. A Forced Ranking Scale is then utilised to assess the effects of these complexity traits on the identified complexity strings. This method facilitates the determination of the impact of any set of traits on a specific complexity string, ultimately leading to the calculation of a revised makespan. The resulting affected schedule vividly demonstrates the discrete consequences of these traits within the determined complexity strings while also aiding in identifying activities directly and indirectly affected by the traits. The thesis offers methods for identifying and associating complexity strings with distinct complexity traits. Furthermore, it outlines a procedure for calculating and substantiating the influence of these complexity traits on a project's schedule makespan."]},{"key":"dc:title","label":"Title","values":["Scheduling techniques that accommodate complexity: industrial practices and new approaches."]}]}],"canonical_facts":{"dc:contributor.advisor":["Q.M.M. Zaman, R. Laing, D. Ahiaga-Dagbui and P. Boateng"],"dc:contributor.sponsor":["No Funder Acknowledged (Outputs)"],"dc:creator":["Lambert, Jeremy Clifford"],"dc:creator.authoridentifier":["0000-0002-1048-1632"],"dc:date":["2025-02-28"],"dc:date.issued":["2025"],"dc:description.abstract":["Complexity is a recognized factor that impacts project performance, yet quantifying this impact remains elusive. The Newtonian certainty of breaking down a project's schedule through a work breakdown structure into discrete activities fails to acknowledge the interwoven nature, iterative behaviour, and emergent state that arises when dealing with complexity. To understand the impact of complexity on a project's schedule, it is essential to identify, assign, and quantify complexity traits relative to the project's network. Through the research supporting the thesis, a comprehensive literature search has identified a set of complexity traits, and further research has isolated discrete complexity strings within project schedule networks. Assigning these complexity traits to these strings unveils the DNA of complexity within any given project schedule. A two-stage Delphi Method is employed to allocate the identified complexity traits to the discrete complexity strings. The two stages involve initially assigning traits to specific strings and subsequently recognizing the complexity strings with the most profound impact. A Forced Ranking Scale is then utilised to assess the effects of these complexity traits on the identified complexity strings. 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