Although mobile applications (apps) for crime reporting can enhance safety and foster social cohesion in urban communities, adoption of existing crime-reporting apps remains low because they overemphasize technological features at the expense of social realities. To address this problem, the study builds on socio-technical systems theory to addresses this problem by developing a Socio-Technical Evaluation Framework (STEF) in partnership with urban residents that can be used to guide the design and evaluation of these apps. The study combines qualitative (focus groups, interviews, app review analysis, and co-creation workshops) with quantitative methods (surveys and structural equation modeling) to identify and validate the key social and technical factors crucial to adopting crime-reporting apps. The results revealed that although users initially found these apps to be helpful, sustained use is driven by perceived value related to anonymity, recency, autonomy, camaraderie, and accessibility. Partial Least Squares Structural Equation Modeling analysis confirmed that perceived value and Unified Theory of Acceptance and Use of Technology (UTAUT) constructs predict both behavioral intention (BI) and actual use, with the model explaining 74% of the variance in BI and 51% of the variance in actual use. The STEF framework offers a transferable methodology that can be used to develop effective, community-driven digital solutions.
","abstract_html":"<p>Although mobile applications (apps) for crime reporting can enhance safety and foster social cohesion in urban communities, adoption of existing crime-reporting apps remains low because they overemphasize technological features at the expense of social realities. To address this problem, the study builds on socio-technical systems theory to addresses this problem by developing a Socio-Technical Evaluation Framework (STEF) in partnership with urban residents that can be used to guide the design and evaluation of these apps. The study combines qualitative (focus groups, interviews, app review analysis, and co-creation workshops) with quantitative methods (surveys and structural equation modeling) to identify and validate the key social and technical factors crucial to adopting crime-reporting apps. The results revealed that although users initially found these apps to be helpful, sustained use is driven by perceived value related to anonymity, recency, autonomy, camaraderie, and accessibility. Partial Least Squares Structural Equation Modeling analysis confirmed that perceived value and Unified Theory of Acceptance and Use of Technology (UTAUT) constructs predict both behavioral intention (BI) and actual use, with the model explaining 74% of the variance in BI and 51% of the variance in actual use. The STEF framework offers a transferable methodology that can be used to develop effective, community-driven digital solutions.</p>","abstract_has_math":false,"creators":["DAVID-BANJO, OLALEKAN OLUWASEUN"],"institution":null,"degree_name":"Information Systems and Technology, PhD","degree_level":"Open Access Dissertation","degree_discipline":"Center for Information Systems and Technology","degree_department":null,"school":null,"contributors":["Juliette M Gutierrez","Nagla S Alnosayan","Paul Witman"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-01-01T08:00:00Z","date_published":"2025-01-01T08:00:00Z","updated_at":"2026-07-24T01:41:17Z","subjects":["Action design research","Crime-reporting mobile apps","Sociotechnical factors","Technology adoption","Criminology"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarship.claremont.edu/cgu_etd/1044","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Juliette M Gutierrez","Nagla S Alnosayan","Paul Witman"]},{"key":"dc:creator","label":"Author","values":["DAVID-BANJO, OLALEKAN OLUWASEUN"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2026-05-13T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Center for Information Systems and Technology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Information Systems and Technology, PhD"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Action design research","Crime-reporting mobile apps","Sociotechnical factors","Technology adoption","Criminology"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarship.claremont.edu/cgu_etd/1044"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Although mobile applications (apps) for crime reporting can enhance safety and foster social cohesion in urban communities, adoption of existing crime-reporting apps remains low because they overemphasize technological features at the expense of social realities. To address this problem, the study builds on socio-technical systems theory to addresses this problem by developing a Socio-Technical Evaluation Framework (STEF) in partnership with urban residents that can be used to guide the design and evaluation of these apps. The study combines qualitative (focus groups, interviews, app review analysis, and co-creation workshops) with quantitative methods (surveys and structural equation modeling) to identify and validate the key social and technical factors crucial to adopting crime-reporting apps. The results revealed that although users initially found these apps to be helpful, sustained use is driven by perceived value related to anonymity, recency, autonomy, camaraderie, and accessibility. Partial Least Squares Structural Equation Modeling analysis confirmed that perceived value and Unified Theory of Acceptance and Use of Technology (UTAUT) constructs predict both behavioral intention (BI) and actual use, with the model explaining 74% of the variance in BI and 51% of the variance in actual use. The STEF framework offers a transferable methodology that can be used to develop effective, community-driven digital solutions.
"]},{"key":"dc:title","label":"Title","values":["Co-Creating a Socio-Technical Framework for the Design and Evaluation of Crime-Reporting Mobile Apps in Urban Residential Communities"]}]}],"canonical_facts":{"dc:contributor":["Juliette M Gutierrez","Nagla S Alnosayan","Paul Witman"],"dc:creator":["DAVID-BANJO, OLALEKAN OLUWASEUN"],"dc:date.available":["2026-05-13T07:00:00Z"],"dc:description.abstract":["Although mobile applications (apps) for crime reporting can enhance safety and foster social cohesion in urban communities, adoption of existing crime-reporting apps remains low because they overemphasize technological features at the expense of social realities. To address this problem, the study builds on socio-technical systems theory to addresses this problem by developing a Socio-Technical Evaluation Framework (STEF) in partnership with urban residents that can be used to guide the design and evaluation of these apps. The study combines qualitative (focus groups, interviews, app review analysis, and co-creation workshops) with quantitative methods (surveys and structural equation modeling) to identify and validate the key social and technical factors crucial to adopting crime-reporting apps. The results revealed that although users initially found these apps to be helpful, sustained use is driven by perceived value related to anonymity, recency, autonomy, camaraderie, and accessibility. Partial Least Squares Structural Equation Modeling analysis confirmed that perceived value and Unified Theory of Acceptance and Use of Technology (UTAUT) constructs predict both behavioral intention (BI) and actual use, with the model explaining 74% of the variance in BI and 51% of the variance in actual use. The STEF framework offers a transferable methodology that can be used to develop effective, community-driven digital solutions.
"],"dc:identifier":["https://scholarship.claremont.edu/cgu_etd/1044"],"dc:subject":["Action design research","Crime-reporting mobile apps","Sociotechnical factors","Technology adoption","Criminology"],"dc:title":["Co-Creating a Socio-Technical Framework for the Design and Evaluation of Crime-Reporting Mobile Apps in Urban Residential Communities"],"thesis:degree_discipline":["Center for Information Systems and Technology"],"thesis:degree_level":["Open Access Dissertation"],"thesis:degree_name":["Information Systems and Technology, PhD"]},"updated_at":"2026-07-24T01:41:17Z"}