Systems

Rising geopolitical risks have become a defining feature of the global business environment, yet how firms—particularly those from latecomer economies—adjust their innovation strategies under such conditions remains insufficiently understood. Integrating resource dependence theory with the innovation ecosystem perspective, we propose that geopolitical risk induce firms to engage in cross-industry innovation as a strategic response to mitigate their reliance on international technological ecosystems, which traditionally provide cross-industry complementarities but are increasingly subject to disruption. Analyzing a panel of 12,354 Chinese listed manufacturing firms from 2012 to 2022, and employing fixed-effects negative binomial regression models implemented in Stata 18, we find that firms exposed to higher levels of perceived geopolitical risk are more likely to pursue innovations beyond their industry’s technological boundaries in subsequent years. This effect is weakened by industry technological complexity but strengthened by the firm’s nationalism, reflecting both reactive responses to external uncertainty and proactive efforts toward technological self-reliance. Our study contributes to innovation research by revealing how geopolitical forces reshape firms’ innovation trajectories and by extending resource dependence theory to the context of ecosystem-based interdependence. From a policy perspective, governments can promote rational and constructive nationalist narratives that encourage firms to commit to innovation in strategically vulnerable technologies.

This study investigates the impact of Environmental Policy Stringency (EPS) on GVC functional specialization. We find that EPS promotes high value-added, low-carbon upstream and downstream specialization—supporting the “Porter Hypothesis (PH)”—while simultaneously driving carbon-intensive production to regions with lax regulations, validating the “Pollution Haven Hypothesis (PHH)”. These findings demonstrate that both effects coexist across distinct GVC stages. Heterogeneity analysis reveals that the impacts of EPS vary across policy instruments: market-based instruments primarily promote upstream functional specialization, whereas non-market instruments exert stronger effects on downstream functional specialization. In terms of temporal dynamics, the Paris Agreement intensified the PHH in production activities while catalyzing medium-to-long-term incentives for upstream and downstream specialization. The influence of EPS on GVC structural adjustments has strengthened notably since the Paris Agreement, reflecting a significant temporal lag and long-term efficacy. Mechanistically, low-carbon innovation serves as the primary channel for functional upgrading, an effect significantly amplified by robust national innovation systems (NIS) and entrepreneurship. Meanwhile, NIS and entrepreneurship partly amplify the positive effect of EPS on high-end functional specialization. From a GVC functional perspective, this study offers new evidence reconciling the PH and the PHH.

This study examines the systemic impact of mobile device usage on sleep health and overall wellbeing through a systems thinking (ST) approach. By employing a systems approach, this study offers a novel contribution to this area by exploring the intricate interdependencies among mobile device usage, sleep hygiene practices (a set of everyday behaviors that promote good sleep health), and related health outcomes. To understand the dynamics and the interdependent nature of sleep, health, and holistic wellbeing, the study examines three interrelated cases: (Case 1) mapping factors that negatively influence sleep and their causal relationships; (Case 2) modeling causal loop diagrams (CLDs) to illustrate the interdependencies among sleep duration, sleep quality, and health outcomes; and (Case 3) modeling CLDs and analyzing the impact of nighttime mobile and electronic device usage on sleep patterns and long-term wellbeing. Rather than presenting empirical data, this paper employs an ST methodology and structurally validated qualitative modeling through CLDs to provide a conceptual framework that complements existing correlational studies and informs future public health research and policy interventions. A significant gap exists in this domain regarding the use of ST tools—such as CLDs—in sleep research to capture the complex, interdependent relationships between sleep health factors and overall health. By focusing on CLDs as one of the ST methods, this paper highlights the dynamic feedback loops through which behavioral, psychological, and environmental factors interact—often negatively reinforced over time by nighttime mobile device usage—to shape sleep quality and overall wellbeing. It underscores the need for novel interdisciplinary strategies and the application of ST to design interventions to mitigate sleep-related health risks and promote digital and holistic wellbeing.