Search results

The development and evolution of stakeholder collaborative innovation in megaprojects is impacted by various influencing factors. The effect of influencing factors on collaborative innovation performance (CIP) in megaprojects is not a simplistic linear relationship but an iterative and non-linear relationship that requires a dynamic perspective to analyze. Therefore, this paper adopts the system dynamic (SD) approach to investigate the dynamic and interactive relationships between the CIP and the influencing factors.

The study first develops a research framework with the system boundary of “CIP system – organizational collaboration subsystem – knowledge collaboration subsystem – strategic collaboration subsystem”. Then, the causal relationship model, the stock-flow model, and the mathematical equations were determined based on the literature review and the expert interviews. Finally, five performance improvement scenarios were designed according to the practice context of CIP in megaprojects, and simulations were performed using the Vensim PLE software to investigate the CIP from a dynamic perspective.

The findings reveal that the effect of different influencing factors on CIP grows non-linearly, with the cumulative effect becoming more pronounced as time advances. The incentive mechanism has the most significant effect, and the combined effect of multiple influencing factors has a highly significant facilitating effect on improving CIP. Strategic collaboration, organizational collaboration and knowledge collaboration are mutually conditional and reinforcing with each other, which ultimately promotes the improvement of CIP.

This study uncovers the inherent pattern and the interactive dynamic mechanism of factors for improving CIP in the context of megaprojects. It enriches the theoretical research in the area of collaborative innovation in megaprojects and provides practical management strategies for improving CIP.

Due to excessive carbon dioxide emissions, the world is facing environmental devastation. Energy and environmental innovations are considered to be critical tools in combating the growing CO₂ emissions. Developing these innovations requires extremely high investments in research and development processes, where knowledge is generated as one of the important outputs. This knowledge serves as a basis for innovation development and raising awareness among all relevant stakeholders about excessive environmental degradation. One of the significant sources of knowledge is scientific publications. Therefore, the aim of this research is to examine whether increased CO₂ emissions stimulate the scientific community to publish a greater number of papers, as well as whether the knowledge contained in these publications is utilized in reducing CO₂ emissions. The sample consists of G7 member countries. The time frame of the research is 1996–2019. The dynamic properties of the vector autoregression (VAR) models were summarized using impulse response function and variance decomposition forecast error. In most G7 countries, it has been determined that an increase in scientific production in environmental science and energy leads to a reduction in CO₂ emissions. On the other hand, increased CO₂ emissions affect higher scientific productivity in environmental science and energy only in Canada.

This study empirically investigates the impacts of technological innovation and operational efficiency on environmental performance and the moderating effects of environmental orientation.

We develop a conceptual framework based on the Porter Hypothesis. We collect a sample of 850 listed firms in China between 2010 and 2019. The fixed effect model was used to analyse the data.

The empirical findings reveal that technological innovation indirectly enhances environmental performance through operational efficiency and partially mediates this impact. We also find that environmental orientation strengthens the positive impacts of technological innovation and operational efficiency on environmental performance.

This study contributes to the literature by revealing that technological innovation is positively associated with operational efficiency and environmental performance, which suggests that technological innovation can simultaneously enhance business and environmental performance. Hence, this study provides empirical support for the Porter Hypothesis. The results also extend the Porter Hypothesis by revealing how technological innovation affects environmental performance and under what conditions technological innovation has a greater impact on environmental performance.

While implementing green innovation-driven strategies when facing growing grim environmental problems and the realistic demands of achieving high-quality development is increasingly urgent, changing abruptly is inevitably detrimental to the smooth functioning of social and economic development. Restrained by resources, innovation-driven strategy is a huge strategy for an organization to shift from traditional technological innovation to green innovation. Supports and implementation in green technology investment would necessarily crowd out other business investment and lead to reduction of innovation outputs and mount of financial uncertainty. Under the guidance of harmonious balance, the equilibrium allocation between green research and non-green counterpart is badly needed to be addressed for decision-makers inside and outside the organizations. The differentiated inputs of them would lead to different effects on organizational performance in practice.

The authors first conducted a Hausman test on green research intensity (GRI) and innovation performance, economic performance, social performance, and environmental performance, respectively. Adopting the fixed effects model for estimation seems accurate, if there is no significant heteroscedasticity shown in the BP test. The authors then adopted the least square dummy variable method to handle individual heterogeneity (Xia et al., 2020). After controlling the industry effect and time effect simultaneously, the results were consistent with that of fixed effects model, thereby eliminating the impact of heteroscedasticity.

The authors construct a multi-dimensional performance system—innovation performance, economic performance, social performance, and environmental performance—to probe into the influence of GRI from the resource-based view and allocation theory. Different performance does not benefit equally from increasing the intensity of green research. Performance increase may squeeze out the quantity of total innovation but can compensate quality for knowledge spillovers of green technology. The organization's growth and long-term value may be beneficial from the increase, but not the short-term financial performance. While the relationship between GRI and social performance has the characteristic of reverse U-curve, there has to be some scale of green research to gain considerable and nonlinear environmental performance. Low level of green research may increase pollution until green research has cross over the inflection point. These relationships are intensely moderated by the environmental regulation.

Because of the focus of this study is on the organizational performance of green research, the analysis comes with some limitations that should be addressed in future research. Data were inter-professional, with large enterprises and small businesses innovating green technology at the same time. Though the hypotheses presented here were grounded in existing theoretical rationale, the generality of this study cannot be assumed. Multi-performance of green activities in small- and medium-sized businesses should be further explored. Additionally, concrete index of the corresponding evaluation system constructed here contribute more to practical activities of green innovation. Refinement of synergy performance index is the task for future work. Further, grounded in Chinese context, the authors' results could be compared with other scenario with institutional heterogeneity to provide detailed evidences for institutional theory. Future studies could also move forward to longitudinal case study to delicately investigate the performance differentiation of green research when in different development stage.

First, what and how the authors do is novel as the authors use listed Chinese manufacturing companies to probe into the complex relationship between GRI and multiple performance rather than discussing the performance of green innovation input from a single perspective merely. Second, the authors systematically define the performance as economic performance, environmental performance, social performance and innovation performance in depth, which consider adequately the tangible and intangible value as well as internal and external benefits of green research. And finally, in the context of environmental regulation, the study discusses the differentiation of the increase of green research intensity from the perspective of resource constraints, providing reference for optimizing the resource allocation in green and non-green research and solving the decoupling between earnest social appeal and sluggish or reluctant green behaviors.