Sports apps are third-party applications for smartphones or wearables that can help users record fitness data and guide their exercise behavior. Many Chinese college students are compelled to use sports apps for running exercises to improve their physical health and cultivate extracurricular exercise habits; however, the acceptance and use of sports apps by college students in mandatory situations requires elucidation. We explored the influencing factors of university students’ behavioral intention and usage behavior to use sports apps in mandatory situations by combining the unified theory of acceptance and use of technology and the Self-Determination Theory. A questionnaire survey was conducted among 249 students of Liaoning University of Technology by using non-probabilistic convenient sampling. Data analysis was performed by employing partial least squares structural equation modeling. The results showed that (1) the research model explained 66% (R2 = 0.66) of the variance in behavioral intention and 30% (R2 = 0.30) of the variance in usage behavior; (2) performance expectancy, effort expectancy, social influence, and autonomous motivation significantly positively affected behavioral intention, while controlled motivation negatively affected behavioral intention; and (3) behavioral intention, autonomous motivation, and controlled motivation significantly positively affected usage behavior. The influence of facilitating conditions on usage behavior was non-significant. The results will help technical developers and schools to better understand the influencing factors of college students’ use of sports apps in mandatory situations, and formulate corresponding improvement strategies and policies to further promote the role sports apps play in college students’ exercise behavior.

Green control techniques (GCT) are an important supporting technology to ensure sustainable agricultural development. To advance the adoption of GCT, it is crucial to understand the intention of farmers to adopt GCT and its related determinants. However, current research is mostly limited to using a single theoretical model to explore farmers’ intentions to adopt GCT, which is not conducive to revealing the determinants of farmers’ intentions to adopt GCT. To address this gap, this study integrates the Theory of Planned Behavior (TPB), the Technology Acceptance Model (TAM), the Innovation Diffusion Theory (IDT), and the Motivational Model (MM) based on research data from 362 rice farmers in Heshan District, Yiyang City, Hunan Province, and uses partial least squares structural equation modeling (PLS-SEM) to empirically test and compare the above models. The model comparison results prove that the TPB (R2 = 0.818, Q2 = 0.705), TAM (R2 = 0.649, Q2 = 0.559), IDT (R2 = 0.782, Q2 = 0.674), and MM (R2 = 0.678, Q2 = 0.584) models all have explanatory power and predictive validity in the context of green control techniques. However, the integrated model (R2 = 0.843, Q2 = 0.725) is found to be superior to these individual theoretical models because it has larger values of R2, Q2, and smaller values of Asymptotically Efficient, Asymptotically Consistent, and provides a multifaceted understanding for identifying the factors influencing adoption intentions. The results of the path analysis show that attitude, perceived behavioral control, perceived usefulness, subjective norm, and visibility significantly and positively influence adoption intentions in both the single and integrated models and are determinants of farmers’ intentions to adopt GCT.