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Institutional actors are critical allies for grassroots movements, but few studies have examined their effects and variations within the non-democratic context. This chapter argues that while institutional allies are heavily constrained and unlikely to give open endorsement to grassroot activists, some institutional activists indirectly facilitate movement mobilization and favorable outcomes in the process of advancing their own political agendas. Drawing upon in-depth interviews conducted in 2008 and 2012, I illustrate this argument by examining the Anti-PX Movement – a landmark grassroots environmental movement against a chemical plant – in Xiamen, China. I find that the environmental institutional actors were constrained and divided, yet some still fostered opportunities for movement mobilization and in turn exploited the opportunity created by the protesters to pursue their policy interests, thus facilitating positive movement outcomes. As long as the claims are not politically subversive to the authoritarian rule, this type of tacit and tactical interaction between institutional activists within the state and grassroot activists on the street is conducive to promoting progressive policy changes.

We take a state-stewardship view on corporate governance and executive compensation in economies with strong political involvement, where state-appointed managers act as responsible “stewards” rather than “agents” of the state.

We test this view on China and find that Chinese managers are remunerated not for maximizing equity value but for increasing the value of state-owned assets.

Managerial compensation depends on political connections and prestige, and on the firms’ contribution to political goals. These effects were attenuated since the market-oriented governance reform.

Economic reform without reforming the human resources policies at the executive level enables the autocratic state to exert political power on corporate decision making, so as to ensure that firms’ business activities fulfill the state’s political objectives.

As a powerful social elite, the state-steward managers in China have the same interests as the state (the government), namely extracting rents that should adhere to the nation (which stands for the society at large or the collective private citizens).

As China has been a communist country with a single ruling party for decades, the ideas of socialism still have a strong impact on how companies are run. The legitimacy of the elite’s privileged rights over private sectors is central to our question.

Chinese executive compensation stimulates not only the maximization of shareholder value but also the preservation of the state’s interests.

The purpose of this study is to explain the following questions: First, whether the executive equity incentive has an impact on enterprise innovation and digital transformation; Second, if there is any influence, whether there is difference between state-owned enterprises and private enterprises in the research conclusions; Third, whether the digital transformation of enterprises has had an intermediary effect between executive equity incentive and enterprise innovation; Fourth, whether the proportion of independent directors in the corporate governance mechanism has a regulatory effect.

In the context of China's promotion of “digital China” construction and high-quality development of economic innovation, this paper takes Shanghai and Shenzhen A-share listed companies in 2011–2019 as a sample, empirically studies the linear and nonlinear relationship between executive equity incentive and enterprise digital transformation and innovation, and further considers the regulatory effect of heterogeneous property rights and the proportion of independent directors, with a view to improving the reform of China's enterprise equity incentive system make contributions to enterprise innovation and digital transformation.

The results show that executive equity incentive has a positive role in promoting enterprise digital transformation and innovation, and enterprise digital transformation has a positive role in promoting enterprise innovation; Digital transformation of enterprises has a partial intermediary effect between executive equity incentive and enterprise innovation.

First, it expands the research on the economic consequences of enterprise salary incentive system. Second, it expands the research on the specific role path of enterprise digital economy transformation. Third, provide new ideas for the reform of corporate governance mechanism.

Cognitive radio (CR) plays a very important role in enabling spectral efficiency in wireless communication networks, where the secondary user (SU) allows the licensed primary users (PUs). The purpose of this paper is to develop a prediction model for spectrum sensing in CR.

This paper proposes a hybrid prediction model, called krill-herd whale optimization-based actor critic neural network and hidden Markov model (KHWO-ACNN-HMM). The spectral bands are determined optimally using the proposed hybrid prediction model for allocating the spectrum bands to the PUs. For better sensing, the eigenvalue based on cooperative sensing used in CR. Finally, a hybrid model is designed by hybridizing KHWO-ACNN and HMM to enhance the accuracy of sensing. The predicted results of KHWO-ACNN and HMM are combined by a fusion model, for which a weighted entropy fusion is employed to determine the free spectrum available in CRs.

The performance of the prediction model is evaluated based on metrics, such as probability of detection, probability of false alarm, throughput and sensing time. The proposed spectrum sensing method achieves maximum probability of detection of 0.9696, minimum probability of false alarm rate as 0.78, minimum throughput of 0.0303 and the maximum sensing time of 650.08 s.

The proposed method is useful in various applications, including authentication applications, wireless medical networks and so on.

A hybrid prediction model is introduced for energy efficient spectrum sensing in CR and the performance of the proposed model is evaluated with the existing models. The proposed hybrid model outperformed the other techniques.

Based on the typical service supply chain (SSC) structure, the authors construct the model of e-tailing SSC to explore the coordination relationship in the supply chain, and big data analysis provides realistic possibilities for the creation of coordination mechanisms.

At the present stage, the e-commerce companies have not yet established a mature SSC system and have not achieved good synergy with other members of the supply chain, the shortage of goods and the greater pressure of express logistics companies coexist. In the case of uncertain online shopping market demand, the authors employ newsboy model, applied in the operations research, to analyze the synergistic mechanism of SSC model.

By analyzing the e-tailing SSC coordination mechanism and adjusting relevant parameters, the authors find that the synergy mechanism can be implemented and optimized. Through numerical example analysis, the authors confirmed the feasibility of the above analysis.

Big data analysis provides a kind of reality for the establishment of online SSC coordination mechanism. The establishment of an online supply chain coordination mechanism can effectively promote the efficient allocation of supplies and better meet consumers' needs.

One of the most marginalized communities in India is the Lesbian, Gay, Bisexual and Transgender (LGBT) community which commonly experiences discrimination. Many studies have countered that the LGBT community faces high discrimination in the banking and financing industry. As a result, this study concentrates on this marginalized community and its acceptance and continuation habit regarding mobile wallets. Consequently, this study has considered continuance intentions as a response to confirm the progress of the mobile-wallet industry. Also, this study tried to study the relationship between behavioral intention (BI) and continuous intention (CI) which is seriously lacks in the library of literature. The research operationalized the stimulus–organism–response (SOR) framework for the conceptual model and surveyed 100 self-proclaimed members of the LGBT community in India. The analysis has been done using the partial least structure (PLS). The findings demonstrate that variables like perceived trust (PT) directly influence the BI. On the other hand, variables like perceived ease of use (PEoU), social influence (SI), and satisfaction (S) doesn’t influence BI of the LGBT Community. The main outcome was a favorable association between BI and CI. It will help the stakeholders to understand how important this new market avenue is and how it can be explored. To ensure safe and secure transactions, a group think tank composed of important parties (financial institutions, mobile-wallet providers, the government, security specialists, etc.) should make recommendations. Mobile-wallet providers will attain benefit from this study’s understanding of user categories and ability to tailor their service offers as per the community.

This study proposes a predictive neural network model reference decoupling control method for the coupling problem between the leg joints of hydraulic quadruped robots, and verifies its decoupling effect..

The machine–hydraulic cross-linking coupling is studied as the coupling behavior of the hydraulically driven quadruped robot, and the mechanical dynamics coupling force of the robot system is controlled as the disturbance force of the hydraulic system through the Jacobian matrix transformation. According to the principle of multivariable decoupling, a prediction-based neural network model reference decoupling control method is proposed; each module of the control algorithm is designed one by one, and the stability of the system is analyzed by the Lyapunov stability theorem.

The simulation and experimental research on the robot joint decoupling control method is carried out, and the prediction-based neural network model reference decoupling control method is compared with the decoupling control method without any decoupling control method. The results show that taking the coupling effect experiment between the hip joint and knee joint as an example, after using the predictive neural network model reference decoupling control method, the phase lag of the hip joint response line was reduced from 20.3° to 14.8°, the amplitude attenuation was reduced from 1.82% to 0.21%, the maximum error of the knee joint coupling line was reduced from 0.67 mm to 0.16 mm and the coupling effect between the hip joint and knee joint was reduced from 1.9% to 0.48%, achieving good decoupling.

The prediction-based neural network model reference decoupling control method proposed in this paper can use the neural network model to predict the next output of the system according to the input and output. Finally, the weights of the neural network are corrected online according to the predicted output and the given reference output, so that the optimization index of the neural network decoupling controller is extremely small, and the purpose of decoupling control is achieved.

Research focuses on factors that affect nascent entrepreneurs’ decision to create a start-up but research in the field of open data contests has not been investigated yet. So, there are no conclusions about the enhancement of entrepreneurship through the hosting of contests. This chapter aims to examine the factors that affect the decision of establishing a start-up by developers who have participated in open data contests. Interviews were conducted with developers who participated in hackathons and they aimed to launch their apps and establish start-ups. The obstacles were the limited support, marketing activities, and the lack of free data.

The purpose of this study is to examine how the implementation of edge computing can enhance the progress of the circular economy within supply chains and to address the challenges and best practices associated with this emerging technology.

This study utilized a streamlined evaluation technique that employed Latent Dirichlet Allocation modeling for thorough content analysis. Extensive searches were conducted among prominent publishers, including IEEE, Elsevier, Springer, Wiley, MDPI and Hindawi, utilizing pertinent keywords associated with edge computing, circular economy, sustainability and supply chain. The search process yielded a total of 103 articles, with the keywords being searched specifically within the titles or abstracts of these articles.

There has been a notable rise in the volume of scholarly articles dedicated to edge computing in the circular economy and supply chain management. After conducting a thorough examination of the published papers, three main research themes were identified, focused on technology, optimization and circular economy and sustainability. Edge computing adoption in supply chains results in a more responsive, efficient and agile supply chain, leading to enhanced decision-making capabilities and improved customer satisfaction. However, the adoption also poses challenges, such as data integration, security concerns, device management, connectivity and cost.

This paper offers valuable insights into the research trends of edge computing in the circular economy and supply chains, highlighting its significant role in optimizing supply chain operations and advancing the circular economy by processing and analyzing real time data generated by the internet of Things, sensors and other state-of-the-art tools and devices.