Search Results (54)

Focusing on the issue that false data injection (FDI) attacks on the secondary controllers of DC microgrids can affect the normal and stable operation of microgrids, a distributed resilient controller for DC microgrids is proposed to ensure that the two control objectives, voltage regulation and current sharing, can still be achieved under the action of time-varying bounded FDI attacks. First, the distributed secondary control problem of the microgrid is viewed as a leader–follower multi-agent consensus problem, and the impact of FDI attacks on the microgrid is analyzed. Second, a fully distributed resilient controller based on an adaptive compensation mechanism is designed to compensate for FDI attacks and mitigate their impact on the microgrid. Next, it is proven through Lyapunov stability theory that the microgrid can operate normally and stably under the designed distributed resilient controller, achieving the two control objectives. Finally, simulation analysis is used to verify the effectiveness of the proposed resilient control method. Full article

To address the trajectory tracking problem of networked unmanned surface vessels (USVs) under false data injection (FDI) attacks, an adaptive neural network-based prescribed performance control scheme is proposed. First, considering the adverse effects of network attacks, system uncertainties, and time-varying disturbances, an adaptive neural network observer is designed to estimate and compensate for the lumped disturbances. Building on this, a dynamic event-triggered mechanism is separately developed for the sensor-to-controller and controller-to-actuator channels, forming a novel dual-channel dynamic event-triggered mechanism (DDETM). This mechanism reduces unnecessary communication overhead and actuator wear caused by frequent data exchanges while enabling thrust allocation for a quantitative analysis of actuator degradation. Furthermore, a control algorithm based on a second-order prescribed performance function (SOPPF) and dynamic surface control (DSC) is proposed to ensure transient and steady-state performance of the tracking error while mitigating the computational complexity associated with the traditional backstepping method. Using Lyapunov theory, it is demonstrated that all signals in the closed-loop system are uniformly ultimately bounded and that Zeno behavior is avoided. Simulation results further validate the effectiveness of the proposed control approach in solving the trajectory tracking problem of USV. Full article

Developed and developing economies use globalization and foreign direct investment (FDI) to pave the way and to maximize economic growth. This study aims to investigate the impact of globalization and FDI on the economic growth of South Africa over the period from 1998 to 2022. The study employed the autoregressive distributed lag (ARDL) approach on annual data from the World Bank and the KOF index of globalization. ARDL tests reveal a long-run positive and statistically significant relationship of 12.7% in the case of economic globalization. This indicates that there is a reasonable level of the emergence of a globalized economy to integrate new and diverse systems, within internal economic growth forces that are supporting the globalization and endogenous growth theories. Political globalization is negative and statistically significant, while social globalization is positive but is used to depress long-run economic growth because of its insignificant status. The novelty of this study is to focus on the impacts of economic, social, and political globalization and FDI on the economic growth of South Africa, through direct and interactive procedures. The findings can be used by South African policymakers and other countries to prioritize reaping the benefits of globalization. These outcomes can be used to sensitize and promote policies that can attract relevant FDI, while enhancing economic growth. Full article

This study investigates the impact of Internet of Things (IoT) demand on Digital Economic Growth (DEG) in Saudi Arabia between 2015 and 2023, employing both linear regression and a panel Autoregressive Distributed Lag (ARDL) model. The results show a long-term, significant, and positive association between IoT adoption and DEG, supported by the Technology Organization Environment (TOE) framework, highlighting the relevance of technology readiness and organizational capacity. Moreover, Internet penetration is a significant driver of digital transformation, aligned with the Diffusion of Innovations (DOI) theory, which emphasizes the role of connectivity in facilitating the adoption of digital devices. IoT will have little or no impact in the short term, but in the long run, the benefits are clear. Furthermore, despite the long- and short-term benefits of 5G deployment indicated by the results, a divergence between 5G deployment and electricity consumption is signaled by the significance of the error-correction term, which may be attributed to infrastructure and deployment prerequisites. Additionally, as an extension of the Resource-Based View (RBV) paradigm, the ultimate drivers of DEG through innovation and strategic resources highlight the importance of Research and Development (R&D) investment and Foreign Direct Investment (FDI) in inducing its growth. In contrast, inflation has an adverse impact on DEG, confirming macroeconomic instability as an obstacle to digital advancement, which relates to the environmental pillar of TOE. Policymakers can maximize Saudi Arabia’s digital economic growth on a sustainable, stronger path by investing in IoT infrastructure, increasing internet access and adoption, enhancing R&D and institutional support, and addressing challenges related to macroeconomic stability and 5G deployment. This study adds to the extant research by empirically evaluating the short- and long-term effects of IoT adoption on Saudi Arabia’s digital economic development, thereby providing insights into the roles of innovation, infrastructure, and institutional support in driving digital transformation. Full article

Sustainable tourism development has emerged as a strategic priority across ASEAN countries, yet the role of green innovation and environmentally responsible investment in shaping tourism outcomes remains underexplored. Existing studies often overlook the spatial interdependencies that characterize regional integration and cross-border environmental dynamics. This study investigates how green patents and green foreign direct investment (FDI) influence sustainable tourism development, both within and across ASEAN nations. Drawing on endogenous growth theory, ecological modernization, and FDI spillover frameworks, the analysis employs a Spatial Durbin Model (SDM) using panel data from 2000 to 2023. The findings reveal that green innovation and green FDI significantly enhance tourism development, with notable spatial spillover effects that benefit neighboring countries. These effects are most pronounced in leading ASEAN economies, where institutional capacity and absorptive readiness amplify the impact of green practices. The relationship is further shaped by economic growth, human capital, and political stability, while environmental degradation and inflation pose constraints. The study underscores the nonlinear and regionally heterogeneous nature of green tourism development, offering policy insights for fostering inclusive, resilient, and environmentally sustainable tourism strategies across ASEAN. Full article

Against the backdrop of unprecedented global FDI volatility—with flows declining 34.7% in 2020 and a further 12% in 2022—and China experiencing its first sustained capital outflow since reform, with foreign enterprises withdrawing over USD 160 billion in the first three quarters of 2023, understanding the complex mechanisms through which EPU affects international investment has become critically important. Existing research predominantly examines unilateral EPU effects while neglecting the bilateral dynamics that characterize modern interconnected economies, creating a significant gap in explaining recent FDI pattern shifts. This study systematically examines the differential impact mechanisms of EPU on China’s FDI inflows using panel data from 20 countries spanning 2005–2023, employing FE models and GMM methods. The research reveals that policy uncertainty affects international investment through two mechanisms: first, a “push effect” whereby relatively higher EPU in home countries drives FDI flows to China (β = 0.002, p < 0.001); second, a “consistency effect” where differences in policy environments between home countries and China impede FDI flows (β = −0.004, p < 0.001), with the latter effect being stronger. Moderating effects analysis demonstrates that institutional quality and bilateral political relations exert complex non-linear moderating effects on the EPU–FDI relationship. Heterogeneity tests reveal that when China’s EPU is relatively low, the negative impact of policy uncertainty is significantly weakened. This study extends real options theory and provides empirical evidence for the dual mechanisms of the EPU–FDI relationship, emphasizing that policy coordination is more important than relative policy advantages for international investment decisions. The findings provide theoretical foundations and practical guidance for policymakers to optimize international investment environments and strengthen policy coordination. Full article

As a significant energy source enabling the global energy transition, efficient shale gas development is critical for diversifying supplies and reducing carbon emissions. Zipper fracturing widely enhances the stimulated reservoir volume (SRV) by generating complex fracture networks of shale reservoirs. However, recent trends of reduced well spacing and increased injection intensity have significantly intensified interwell interference, particularly fracture-driven interactions (FDIs), leading to early production decline and well integrity issues. This study develops a fully coupled hydro–mechanical–damage (HMD) numerical model incorporating an explicit discrete fracture network (DFN), opening and closure of fractures, and an aperture–permeability relationship to capture the nonlinear mechanical behavior of natural fractures and their role in FDIs. After model validation, sensitivity analyses are conducted. Results show that when the horizontal differential stress exceeds 12 MPa, fractures tend to propagate as single dominant planes due to stress concentration, increasing the risks of FDIs and reducing effective SRV. Increasing well spacing from 60 m to 110 m delays or eliminates FDIs while significantly improving reservoir stimulation. Fracture approach angle governs the interaction mechanisms between hydraulic and natural fractures, influencing the deflection and branching behavior of primary fractures. Injection rate exerts a dual influence on fracture extension and FDI risk, requiring an optimized balance between stimulation efficiency and interference control. This work enriches the multi-physics coupling theory of FDIs during fracturing processes, for better understanding the fracturing design and optimization in shale gas production. Full article

With the widespread application of cyber–physical systems (CPS) in the field of automation, security concerns have become increasingly prominent. One critical and urgent challenge is the accurate identification of sensor nodes compromised by false data injection (FDI) attacks in multiple-input multiple-output (MIMO) control systems. Building on the implementation of multi-step sampling and residual-based anomaly detection using a support vector machine (SVM), this paper further introduces the Shapley value evaluation method from cooperative game theory and a voting mechanism, and proposes a method for node attack localization. First, multi-step sampling is conducted within each control period to provide a large amount of effective data for the localization of attacked sensor nodes. Next, the residual between the estimated value of the MIMO system’s full response and the actual value received by the controller is calculated, and an SVM model is used to detect anomalies in the residual. Finally, the Shapley value contribution of each residual to the SVM anomaly detection result is evaluated based on cooperative game theory and combined with a voting mechanism to achieve accurate localization of the attacked sensor nodes. Simulation results demonstrate that the proposed method achieves an anomaly detection accuracy of 96.472% and can accurately localize attacked nodes in both single-node and multi-node attack scenarios, indicating strong robustness and practical applicability. Full article

This paper investigates the impact of global EPU and China’s EPU on China’s FDI inflows, examining whether financial development and political stability moderate these relationships. Using panel data from 212 countries spanning 2009 to 2022, we first establish causal direction through Granger causality tests, then employ instrumental variable estimation to address endogeneity concerns, while conducting heterogeneity analysis across development levels and Belt and Road Initiative participation. We find that both global and domestic EPU significantly reduce China’s FDI inflows, with a 1% increase in China’s EPU leading to a 0.083% decrease in FDI inflows. However, political stability and financial development serve as effective moderators, reducing EPU’s negative impact by up to 60% and 70%, respectively. The effects vary substantially across investor countries: non-developed countries show ten times stronger sensitivity to EPU than developed countries, while Belt and Road Initiative countries demonstrate 86% lower sensitivity than non-BRI countries. This research advances EPU–FDI theory by demonstrating how institutional quality creates “policy buffers” against uncertainty and provides policymakers with evidence that strengthening political stability and financial development can maintain investor confidence during uncertain periods, while strategic international partnerships can insulate investment flows from policy volatility. Full article

Amid comprehensive reforms, artificial intelligence (AI) has emerged as a vital force in solving people’s problems and enhancing quality of life. Yet, theoretical inquiries into the mechanisms by which AI influences social well-being remain limited. Drawing upon cultural lag theory, this study constructs a social well-being index system based on the Gini coefficient objective weighting method. By integrating a moderated mediation model with a spatial econometric model, it examines the mechanisms and impacts of artificial intelligence on social well-being. The findings reveal that AI induces multiple cultural lags and exerts a U-shaped impact on social well-being. AI enhances well-being through the channels of employment opportunities, human capital, and green innovation, while digital inclusion and foreign direct investment (FDI) further reinforce this relationship. Additionally, AI generates spatial spillover effects on social well-being, and the region’s well-being landscape exhibits convergence. However, both digital inclusion and FDI negatively moderate the convergence process, slowing its overall pace. These insights provide substantial practical guidance for crafting informed policies aimed at elevating public well-being. Full article

The relationship between inflation and foreign direct investment (FDI) is not clear-cut in theory. In the U.S., rising inflation coupled with increased economic recovery boosted FDI immediately after the COVID-19 pandemic but suppressed it afterwards. To shed light on the relationship between inflation and the resulting contractionary monetary policy and FDI, three key propositions were put forth for investigation. The propositions rely on relevant scientific literature showing that (1) although the connection between FDI and inflation is complex, a high and sustained inflation depresses incoming FDI due to increases in uncertainty and guarding government policies; (2) there exist significant location-based differences in how this connection manifests; and (3) high inflation and subsequent policies motivate FDI-related strategic action. Thus, we propose that new FDI is expected to be negatively affected by the rising entry cost associated with an inflationary economy that adopts anti-inflationary policies. Second, there exists heterogeneity in the effects of inflation on new FDI across subnational economies with various local characteristics. Third, existing FDI demonstrates strategic actions and expansion at the subnational location and beyond, even under inflationary pressure. We employ a positive comparative analysis based on descriptive statistics and qualitative interpretation of data to examine the status and activities of both new FDI (using subnational aggregated data) and existing foreign businesses (using firm-level data) in the state of New Hampshire during the recent inflation surge of 2022–2023. Our analysis provides empirical evidence supporting our propositions. Key implications are that, during challenging times of inflation and recovery, business leaders and economic development professionals should anticipate strategic actions to expand markets, products, operations, and partnerships. Leaders and professionals should act to take advantage of business actions outside the subnational location, as more companies look to strengthen and diversify their national and international networks. Full article

Although the Middle East is often perceived as politically, economically, and socially unstable, Saudi Arabia offers a different narrative. Inspired by the country’s vision (Vision 2030) and the growing body of research exploring its socio-economic transformation, this article examines how organizational strategy theories and practices can be advanced by inviting researchers to focus on Saudi Arabia’s evolving context. To achieve this, the article addresses three pivotal questions: (a) Why should academics consider conducting research in Saudi Arabia? (b) What research topics could significantly advance organizational strategy theories and practices? (c) What are the primary barriers to conducting research in Saudi Arabia? Using a comprehensive review of existing literature, socio-economic analysis, and an evaluation of Vision 2030 targets, the article identifies three key themes: (1) socio-cultural dynamics and their influence on organizational strategies, (2) economic diversification and its impact on strategic resilience, and (3) the strategic alignment of foreign direct investment (FDI) with expatriate mission success. These findings lead to distinct research agendas linked to relevant theoretical frameworks, including Cross-Cultural Theory, Institutional Theory, and the Resource-Based View. The article concludes by inviting scholars to explore these themes and generate findings that contribute to existing organizational strategy theories and practical solutions, fostering a deeper understanding of organizational strategy within Saudi Arabia and the broader global landscape. Full article

Due to its vulnerability to a variety of cyber attacks, research on cyber security for power systems has become especially crucial. In order to maintain the safe and stable operation of power systems, it is worthwhile to gain insight into the complex characteristics and behaviors of cyber attacks from the attacker’s perspective. The consensus-based distributed state estimation problem is investigated for power systems subject to collaborative attacks. In order to describe such attack behaviors, the denial of service (DoS) attack model for hybrid remote terminal unit (RTU) and phasor measurement unit (PMU) measurements, and the false data injection (FDI) attack model for neighboring estimation information, are constructed. By integrating these two types of attack models, a different consensus-based distributed estimator is designed to accurately estimate the state of the power system under collaborative attacks. Then, through Lyapunov stability analysis theory, a sufficient condition is provided to ensure that the proposed distributed estimator is stable, and a suitable consensus gain matrix is devised. Finally, to confirm the viability and efficacy of the suggested algorithm, a simulation experiment on an IEEE benchmark 14-bus power system is carried out. Full article

As the evolution of smart grids accelerates, distributed energy resources (DERs) emerge as key elements in the transformation of global energy systems. However, the integration of these technologies introduces significant cybersecurity vulnerabilities, notably false data injection (FDI) and a direct load-altering attack (DLAA). Traditional load-altering attacks require a huge attack load and, thus, are not practical to implement. In contrast, in modern DER environments where households become “prosumers” with high-power energy generation, the implications of such attacks are substantially amplified. This paper considers a hybrid cyberattack that includes both FDI and a DLAA, and presents a hierarchical, optimal load adjustment framework that addresses these security concerns. A centralized optimizer first calculates the ideal load-shedding strategies for each substation, which are then securely broadcast to households. To address the complexities at the individual household level, we introduce a novel reinforcement learning algorithm termed Mean Field Deep Deterministic Policy Gradients (MF-DDPG). This algorithm employs mean-field game theory to enable decentrally coordinated decision-making among each household, making it particularly effective in zero-trust scenarios. Through this multifaceted approach, we offer a robust countermeasure against load-altering attacks, thereby enhancing the resilience and stability of advanced smart grids. Full article

An ambitious per capita GDP target has been envisioned by the Chinese government since 2020 to project its sustainable economic growth rate by 2035. Can China fully achieve its goal? This is a question worth investigating. By inserting relevant TABLO modules of the final goods trade, the intermediate goods trade, and factor-strengthening technology spillovers, along with technology absorption thresholds effects of the global value chain, this study builds a global recursive dynamic computational general equilibrium (CGE) model on the basis of GTAP-RD. This approach enables us to consider total factor productivity (TFP) development through the “dual circulation” system, which was pointed out by the Chinese government as the only way for further growth. We simulate China’s technological progress under eight scenarios and use the latest GTAP Version 11 production and trade data (released in April 2023) for 141 countries and regions. The main conclusions are as follows: (1) If China maintains its trade opening policy, the 2035 vision goal can be achieved, with external circulation being more important than internal circulation. (2) The economic growth impacts of external and internal circulation function relatively independently. FDI offers a somewhat stronger synergistic effect on intermediate goods trade compared to final goods trade and consumption. (3) We find that the Regional Comprehensive Economic Partnership is the most important strategic partner for China. (4) FDI is not an effective way to lift the productive services sector’s TFP, and it is more realistic for China to open up the productive services market more widely. (5) China–US decoupling has an enormous global impact, and the United States is always the country that loses the most, with Europe being the group of countries that benefits when there is a large increase in TFP in the US. This study is entirely original in terms of its model structure, simulations, scenarios, and shocks. It aims to fill the gap of extending the application of the CGE model to specific issues, thereby making contributions and supplements to the three theories discussed in the article too. The limitation of this paper lies in the CGE linear description feature, which is concise and elegant and has the characteristics of extrapolation and long-term absorption of disturbances. However, it tends to overlook the randomness, non-convergence, and significant structural disturbances that may occur in future reality. Full article