One of the issues organizations face is identifying the required skills needed for a position and then evaluating whether their personnel have these skills or if there is a “skills gap”. The skills gap is the distance between the position requirements and the skills currently possessed by the worker in that position. While multiple models have been created over the years to address facets of the problem, none of them provide a comprehensive framework to clearly identify the required skills and worker qualifications and then evaluate the degree of similarity. A composite skills gap model has been developed using the Design Science Research Method to combine elements of previous models and to ensure that the resulting model met a set of established criteria. The Skills Gap Analysis Model (SGAM) was evaluated using demonstration data to ensure that it provided a single taxonomy for both position requirements and the worker qualifications, the resulting descriptions were quantifiable and comparable, the data was accurate and actionable, the model framework is adaptable to any domain, and that it is easy to use and not time consuming. The framework provided by the model establishes a theoretical foundation for skills gap analyses that allows for more analytical research in this area. By utilizing the SGAM to identify position requirements and worker qualifications, organizations can move personnel to better suited positions or utilize needed training in the specific areas identified. As technology moves towards increasing automation, robotics and artificial intelligence, this type of model can identify what skills are necessary for “re-tooling” the workforce to meet the needs to support these systems.
","abstract_html":"<p>One of the issues organizations face is identifying the required skills needed for a position and then evaluating whether their personnel have these skills or if there is a “skills gap”. The skills gap is the distance between the position requirements and the skills currently possessed by the worker in that position. While multiple models have been created over the years to address facets of the problem, none of them provide a comprehensive framework to clearly identify the required skills and worker qualifications and then evaluate the degree of similarity. A composite skills gap model has been developed using the Design Science Research Method to combine elements of previous models and to ensure that the resulting model met a set of established criteria. The Skills Gap Analysis Model (SGAM) was evaluated using demonstration data to ensure that it provided a single taxonomy for both position requirements and the worker qualifications, the resulting descriptions were quantifiable and comparable, the data was accurate and actionable, the model framework is adaptable to any domain, and that it is easy to use and not time consuming. The framework provided by the model establishes a theoretical foundation for skills gap analyses that allows for more analytical research in this area. By utilizing the SGAM to identify position requirements and worker qualifications, organizations can move personnel to better suited positions or utilize needed training in the specific areas identified. As technology moves towards increasing automation, robotics and artificial intelligence, this type of model can identify what skills are necessary for “re-tooling” the workforce to meet the needs to support these systems.</p>","abstract_has_math":false,"creators":["McKenney, Martin Joseph"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Engineering Management & Systems Engineering","degree_department":null,"school":null,"contributors":["Holly Handley","Charles Daniels","Pilar Pazos-Lago","Anthony Dean"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-10-01T07:00:00Z","date_published":"2019-10-01T07:00:00Z","updated_at":"2026-07-24T03:35:30Z","subjects":["Required skills","Skills gap","Worker qualifications","Skill gap analysis model","Business Administration, Management, and Operations","Operational Research"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["9781392448694"],"render_values":[{"text":"9781392448694","href":null,"code":true}]}]},"links":{"outbound_url":"https://digitalcommons.odu.edu/emse_etds/168","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Holly Handley","Charles Daniels","Pilar Pazos-Lago","Anthony Dean"]},{"key":"dc:creator","label":"Author","values":["McKenney, Martin Joseph"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2019-10-22T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Engineering Management & Systems Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Required skills","Skills gap","Worker qualifications","Skill gap analysis model","Business Administration, Management, and Operations","Operational Research"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["9781392448694","https://digitalcommons.odu.edu/emse_etds/168"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["One of the issues organizations face is identifying the required skills needed for a position and then evaluating whether their personnel have these skills or if there is a “skills gap”. The skills gap is the distance between the position requirements and the skills currently possessed by the worker in that position. While multiple models have been created over the years to address facets of the problem, none of them provide a comprehensive framework to clearly identify the required skills and worker qualifications and then evaluate the degree of similarity. A composite skills gap model has been developed using the Design Science Research Method to combine elements of previous models and to ensure that the resulting model met a set of established criteria. The Skills Gap Analysis Model (SGAM) was evaluated using demonstration data to ensure that it provided a single taxonomy for both position requirements and the worker qualifications, the resulting descriptions were quantifiable and comparable, the data was accurate and actionable, the model framework is adaptable to any domain, and that it is easy to use and not time consuming. The framework provided by the model establishes a theoretical foundation for skills gap analyses that allows for more analytical research in this area. By utilizing the SGAM to identify position requirements and worker qualifications, organizations can move personnel to better suited positions or utilize needed training in the specific areas identified. As technology moves towards increasing automation, robotics and artificial intelligence, this type of model can identify what skills are necessary for “re-tooling” the workforce to meet the needs to support these systems.
"]},{"key":"dc:title","label":"Title","values":["Identifying and Quantifying Personnel Skills Gaps"]}]}],"canonical_facts":{"dc:contributor":["Holly Handley","Charles Daniels","Pilar Pazos-Lago","Anthony Dean"],"dc:creator":["McKenney, Martin Joseph"],"dc:date.available":["2019-10-22T07:00:00Z"],"dc:description.abstract":["One of the issues organizations face is identifying the required skills needed for a position and then evaluating whether their personnel have these skills or if there is a “skills gap”. The skills gap is the distance between the position requirements and the skills currently possessed by the worker in that position. While multiple models have been created over the years to address facets of the problem, none of them provide a comprehensive framework to clearly identify the required skills and worker qualifications and then evaluate the degree of similarity. A composite skills gap model has been developed using the Design Science Research Method to combine elements of previous models and to ensure that the resulting model met a set of established criteria. The Skills Gap Analysis Model (SGAM) was evaluated using demonstration data to ensure that it provided a single taxonomy for both position requirements and the worker qualifications, the resulting descriptions were quantifiable and comparable, the data was accurate and actionable, the model framework is adaptable to any domain, and that it is easy to use and not time consuming. The framework provided by the model establishes a theoretical foundation for skills gap analyses that allows for more analytical research in this area. By utilizing the SGAM to identify position requirements and worker qualifications, organizations can move personnel to better suited positions or utilize needed training in the specific areas identified. As technology moves towards increasing automation, robotics and artificial intelligence, this type of model can identify what skills are necessary for “re-tooling” the workforce to meet the needs to support these systems.
"],"dc:identifier":["9781392448694","https://digitalcommons.odu.edu/emse_etds/168"],"dc:subject":["Required skills","Skills gap","Worker qualifications","Skill gap analysis model","Business Administration, Management, and Operations","Operational Research"],"dc:title":["Identifying and Quantifying Personnel Skills Gaps"],"thesis:degree_discipline":["Engineering Management & Systems Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T03:35:30Z"}