Innovation has always been a key driver of economic development, particularly in the context of small and medium-sized enterprises (SMEs). Despite their significant contributions, many of these enterprises currently lack strong research and development capabilities, face challenges in innovation investment, and struggle to produce high-quality innovative results. To address these issues and overcome funding obstacles, many SMEs are turning to supply chain finance (SCF) as a supplementary financing method. This study utilizes stata16 and fixed effects models to analyze the impact and mechanism of SCF on enterprise innovation performance (EIP), focusing on companies listed on the SME Board and GEM in Shenzhen, China from 2011 to 2020. The findings reveal that SCF can effectively enhance enterprise innovation output, facilitating the conversion of resources into high-quality innovation results. Additionally, the study demonstrates that supply chain concentration acts as a mediator between SCF and EIP. Moreover, SCF is found to significantly boost EIP with low supplier concentrations and high customer concentrations. This suggests that SMEs encounter obstacles to innovation from suppliers and customers, and SCF may not fully address the challenges posed by these relationships. Overall, this research offers new empirical insights into the economic implications of companies adopting SCF, providing valuable guidance for enterprises in optimizing innovation decisions and for the government in enhancing supplier and customer information disclosure systems.
This paper aims to investigate the impact of China’s central state-owned enterprises (SOEs) relocation policy from the capital city of Beijing on the economy and local fiscal revenue. We find that these enterprises play a critical role in implementing national strategies, promoting industrial upgrading, and enhancing the competitiveness of the industry chain. At the same time, their relocation has also dispersed the pressure of economic development in Beijing, promoted regional economic coordination and development, and increased local fiscal revenue. However, attention should be paid to the particularity and diversity of local areas in the process of policy formulation to avoid “one-size-fits-all” solutions. Therefore, when formulating corresponding policies, the central government should guide enterprises to handle relocation issues correctly and safeguard the legitimate rights and interests of employees and their families. Meanwhile, local governments should also formulate corresponding support policies to facilitate enterprise settlement. The ultimate goal is to solve problems and contradictions through development and achieve common prosperity. Therefore, we suggest that the government and enterprises work together to bring prosperity to everyone and jointly promote the sustainable development of the Chinese economy.
Since the proposal of the low-carbon economy plan, all countries have deeply realized that the economic model of high energy and high emission poses a threat to human life. Therefore, in order to enable the economy to have a longer-term development and comply with international low-carbon policies, enterprises need to speed up the transformation from a high-carbon to a low-carbon economy. Unfortunately, due to the massive volume of data, developing a low-carbon economic enterprise management model might be challenging, and there is no way to get more precise forecast data. This study tackles the challenge of developing a low-carbon enterprise management mode based on the grey digital paradigm, with the aim of finding solutions to these issues. This paper adopts the method of grey digital model, analyzes the strategy of the enterprise to build the model, and makes a comparative experiment on the accuracy and performance of the model in this paper. The results show that the values of MAPE, MSE and MAE of the model in this paper are the lowest. And the r^2 of the model in this paper is also the highest. The MAPE value of the model in this paper is 0.275, the MSE is 0.001, and the MAE is 0.003. These three indicators are much lower than other models, indicating that the model has high prediction accuracy. r2 is 0.9997, which is much higher than other models, indicating that the performance of this model is superior. With the support of this model, the efficiency of building an enterprise model has been effectively improved. As a result, developing an enterprise management model for the low-carbon economy based on the gray numerical model can offer businesses new perspectives into how to quicken the shift to the low-carbon economy.
Despite many investigations concerning antecedents of organizational commitment in the workplace, very few studies so far have analyzed the direct or indirect impact of HR change leadership role on organizational commitment via HR attribution. Therefore, given the reciprocal principle of social exchange theory, attribution theory and signal theory, this study formulated hypotheses and a model to test the relationships between included variables by employing the mixed-method approach. In-depth interviews were initially conducted to develop questionnaires to collect quantitative data. Employing PLS-SEM to analyze the data collected from 1058 employees working in 24 sustainable enterprises in Vietnam, the findings show that the degree of adopting HR change leadership role was positive, directly affecting organizational commitment. Also, both well-being and performance HR attribution play partially mediated roles in the relationship. The findings suggest that the organizational commitment depends on not only how the degree of adopting HR change leadership role is executed, but also how employees perceive and interpret the underlying management intent of these practices. In a sustainable context, adopting HR change leadership role plays a critical role in shaping employees’ interpretations of sustainable HR practices and their subsequent attributions. Besides, employees’ belief on why are sustainable HRM practices implemented has an influence on the organizational commitment that in turn contributes to the overall sustainable performance.
State-owned enterprises (SOEs) manage significant portion of world economy, including in the developing countries. SOEs are expected to be active and play significant role in improving the country’s economic performance and welfare through enhancing innovation performance. However, closed innovation process and lack of collaboration hinders SOEs to reach satisfying innovation performance level. This paper explores the construction and role of innovation ecosystem in the strategic entrepreneurship process of SOEs, of which is represented by dynamic capability framework, business model innovation, and collaborative advantage. Based on the analysis, this paper concluded that the collaboration between actors in the Innovation Ecosystem (IE) has positive effect to strengthening SOE’s Sensing Capabilities (SC) related to the process of exploring and identifying innovation opportunities. The increase of Sensing Capabilities (SC) will play significant role as input or antecedent on formulating proactive Innovation Strategy (IS) in orchestrating SOE’s innovation process. SOEs which has implementing proactive Innovation Strategy (IS) will be able to build collaboration and finding right Business Model Innovation (BMI). Finally, by building collaboration with other actors through the innovative business model has significant role to increase SOE’s Collaborative Advantage (CA), which considered as a proxy for competitiveness of SOEs.
Sustainable development has attracted widespread attention worldwide, and the circular economy has become one of the essential policies of many countries. Small and medium-sized enterprises are important drivers of world economic growth and can significantly impact the environment. Therefore, SMEs are critical players in implementing a circular economy as the basis for creating a sustainable society. Although a wealth of research on SME environmental management issues can be found in the literature, more must be known about the infusion of green practices in SMEs. The primary purpose of this study is to explore the green practice infusion of Taiwanese SMEs, a context that is particularly relevant due to Taiwan’s strong focus on environmental sustainability and its circular economy industrial development policy. Through a questionnaire survey, this study examined the factors that influence green practice infusion behavior in Taiwanese SMEs and the impact of green practice infusion on circular economy performance. The findings show that the relative advantages and compatibility of the circular economy, organizational support, human resource quality, regulatory pressure, and government support significantly impact the green practice infusion of Taiwanese SMEs. The effects of complexity, customer pressure, and environmental uncertainty on SMEs’ infusion of green practices are not statistically significant. Circular economy performance is positively correlated with green practice infusion. This study can broaden the research scope of SMEs’ environmental management and contribute to a deeper understanding of SMEs’ green practice infusion and circular economy.
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