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This study aims to explore the effect of digitalization on the promotion of enterprise R&D cooperation, and it analyzes the microimpact mechanism and boundary conditions of enterprise digitalization on enterprise R&D cooperation.

Based on survey data sourced from the World Bank Enterprise Surveys of the business environment of Chinese enterprises in 2012, this study applies multiple regression methods to test theoretical hypotheses.

Enterprise digitalization positively affects the breadth and intensity of enterprise R&D cooperation. Employees’ digital literacy plays an intermediary role between enterprise digitalization and enterprise R&D cooperation. The subordinate attributes of enterprises weaken the positive relationship between enterprise digitalization and the breadth and intensity of enterprise R&D cooperation. The shareholding of state-owned enterprises reinforces the positive relationship between digitalization and the intensity of enterprise R&D cooperation. However, such shareholding shows no significant regulatory effect on digitalization and the breadth of enterprise R&D cooperation.

Focusing on the digital transformation of the enterprise, this study discusses its impact mechanism on enterprise R&D cooperation, including the impact on the intensity and breadth of R&D cooperation. The study further examines the regulatory effect of organizational inertia on enterprise digital and R&D cooperation from two aspects: resource rigidity and routine rigidity. It emphasizes the significance of the digital literacy of employees in enterprise digitalization and discusses the micromechanism of enterprise digitalization and enterprise R&D cooperation.

This study aims to empirically study the effect of process constraints and the combinative effects of different constraints on enterprise digital transformation.

This paper selects the World Bank's business environment survey of Chinese enterprises in 2012 as the research sample to empirically study the effect of process constraints and different kinds of constraints on enterprise digital transformation.

The authors find that process constraints have an inverted U-shaped effect on enterprise digital transformation and that employee digital literacy plays an intermediary role in this process. That is, process constraints have a too-much-of-a-good-thing effect on employees' digital literacy, which further affects enterprise digital transformation. The increase in the number of input and output constraints will make the inverted U-shaped relationship between the process constraint and digital transformation steeper.

The constraints faced by enterprises are everywhere and of many kinds. This paper not only discusses the influence of process constraints on enterprise digital transformation but also analyzes the interactive influence of different kinds of constraints on enterprise digital transformation and explores its micromechanism. This approach is helpful for enterprise managers in thinking about how to make full use of different kinds of constraints to activate the power of enterprise digital transformation, regard constraints as challenges and opportunities, and use them to stimulate the ability to improve the resource integration and utilization.

With China’s economic growth slowing down and the growth rate of fiscal revenue decreasing, the pressure on local government debts is further increasing. Under this background, it is of great significance to clarify the relation between local government debts and China’s economic growth in order to give full play to the positive role of local debts in stabling growth. The paper aims to discuss this issue.

Therefore, this paper explores the impact of Chinese local government debt on economic growth from theoretical and empirical aspects, respectively, and compares the regional differences between different debts and economic growth dynamics.

In the theoretical model part, this paper constructs a three-sector dynamic game model, under the two circumstances of whether local government is subject to debt constraints, and examines the relation between local government debt and economic growth and other variables through numerical simulation. Research shows that when the government is not constrained by debt, there is an inverted “U” relation between government debt and economic growth. When the government is constrained by debt, the economic growth rate gradually decreases as the government debt increases.

In the theoretical analysis part, this paper tries to estimate the amount of local debts under different calibers and examines the impact of different types of local government debts on China’s economic growth and their regional differences. The results show that excessive accumulation of government hidden debts in the eastern region is not conducive to economic growth, while explicit debts in the central and western regions significantly contribute to local economic growth. The results of empirical analysis are basically consistent with the predictions of the theoretical model.

Project portfolio benefit (PPB) evaluation is crucial for project portfolio management decisions. However, PPB is complex in composition and affected by synergy and ambidexterity. Ignoring these characteristics can result in inaccurate assessments, impeding the management and optimization of benefit. Considering the above complexity of PPB evaluation, this study aims to propose a refined PPB evaluation model to provide decision support for organizations.

A back propagation neural network optimized via genetic algorithm and pruning algorithm (P-GA-BPNN) is constructed for PPB evaluation. First, the benefit evaluation criteria are established. Second, the inputs and expected outputs for model training and testing are determined. Then, based on the optimization of BPNN via genetic algorithm and pruning algorithm, a PPB evaluation model is constructed considering the impacts of ambidexterity and synergy on PPB. Finally, a numerical example was applied to validate the model.

The results indicate that the proposed model can be used for effective PPB evaluation. Moreover, it shows superiority in terms of MSE and fitting effect through extensive comparative experiments with BPNN, GA-BPNN, and SVM models. The robustness of the model is also demonstrated via data random disturbance experiment and 10-cross-validation. Therefore, the proposed model could serve as a valuable decision-making tool for PPB management.

This study extends prior research by integrating the impacts of synergy and ambidexterity on PPB when conducting PPB evaluation, which facilitates to manage and enhance PPB. Besides, the structural redundancy of existing assessment methods is solved through the dynamic optimization of the network structure via the pruning algorithm, enhancing the effectiveness of PPB decision-making tools.

The purpose of this paper is to evaluate the impact of corruption on the environmental quality in Tunisia. Indeed, the post-revolution period is characterized by a remarkable increase in the rates of corruption.

The direct and indirect effects of control corruption on economic growth and CO₂ emissions in Tunisia have been examined using the autoregressive distributed lag (ARDL) cointegration framework among corruption, growth and CO₂ emissions.

Results substantiate a positive and significant relationship between control of corruption and economic growth, a negative and significant relationship between control of corruption and environmental quality (CO₂) and a negative and significant relationship between control of corruption and energy consumption. The findings suggest that while the control of corruption contributes to economic growth, its positive effect could be transposed indirectly via its impacts on environmental quality.

A strategy against corruption will reduce CO₂ emissions; however, its positive effect on economic growth indirectly contributes to reverse this relationship.