Investigating the longitudinal effectiveness of a regional semiconductor consortium: a mixed-methods study of members’ perspectives and student enrollment trends
Jin Liu et al.
What the paper says
Purpose The US semiconductor industry faces a critical workforce shortage, prompting national initiatives like the CHIPS Act to support workforce development. In response, a regional multistakeholder consortium was launched in 2023 to address local workforce needs by uniting community colleges, universities and industry. This study aims to examine the consortium’s longitudinal effectiveness over a year using surveys, interviews and student enrollment data. Design/methodology/approach A mixed-methods design was used. The authors used de-identified student-level data from partner community colleges to examine enrollment trends in semiconductor-related programs in relation to consortium activities. Survey data were collected from 11 consortium members, and seven of these participants also completed interviews at three points between Fall 2023 and Fall 2024. The analysis focused on five domains comprising consortium effectiveness: Vision, Collaboration, Plurality, Engagement and Accountability and Capacity. Findings Results showed a 53.7% increase in student enrollment in semiconductor-related programs with significant improvements in perceived effectiveness across five domains. Qualitative findings reinforced these trends. The consortium’s vision matured from conceptual alignment to strategic action, and collaboration deepened through trust and seamless interdependence. Participants increasingly recognized and valued diverse institutional approaches, fostered a culture of shared accountability, and transitioned from foundational infrastructure development to scalable capacity-building. Integrated analysis revealed strong alignment between quantitative and qualitative data, with individual-level reflections further corroborating improvements across domains. Originality/value These findings inform future efforts to build sustainable ecosystems in high-demand technical fields.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.