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The demand for oil in agricultural production increases continuously with the world oil price soaring, reflecting a rigid growth characteristic, but there are no clear reasons for this. The purpose of this paper is to assess the essential reasons of this issue in theoretical and empirical perspectives.

The paper develops the model of derived demand for petroleum in agro‐production; analyzes the effect on agricultural labor‐machinery due to the changes in relative price of input factors; and reveals the reasons for the rigid growth of the demand for farm diesel; as well as estimates the substitution of agricultural machine for labor.

The results indicate that the rigid growth characteristic of the demand for farm diesel is due to the adjustment of the product and factor markets; and the most important reason is the changes in structure of the agro‐production inputs caused by the relative soaring price of agricultural labor‐machinery.

The government should attach importance to its impact on farmers and take effective measures to insure the stable development of agricultural production.

This research investigates the main reasons for the rigid growth characteristic of demand for oil in China's agro‐production from a novelty perspective. The proposed conceptual model is unique, it analyzes the substitution of agricultural mechanical for labor from the perspective of changes in relative price, and selects the two level constant elasticity substitution production functions to estimate the substitution of agricultural machinery for labor.

Risk perception is an essential factor affecting how individuals evaluate risk, make decisions and behave. The impact of risk perception on customer purchase behavior has been widely studied; however, the association has been debated. Therefore, the purpose of this paper is to examine the relationship between risk perception and customer purchase behavior and to examine factors that could moderate it.

This study conducted a meta-analysis of this relationship and examined factors that could moderate it. Six databases were comprehensively searched. Two reviewers independently selected the studies for inclusion, extracted data and assessed quality. Pearson's r was used as the effect estimate. A total of 33 studies were included in the meta-analysis.

The results revealed a negative relationship between risk perception and customer purchase behavior. The geographical region, purchase channel and country development level affected the relationship. The correlation between perceived risk and purchase behavior in European consumers was the highest, followed by the correlation in American consumers; the weakest correlation was found in Asian consumers. For consumers in developed countries, perceived risk had a stronger negative influence on customer purchase behavior than that for consumers in developing countries. The perceived risk of online purchase channels had a stronger negative impact on customer purchase behavior than that of offline purchase channels.

Risk perception is a useful context in which to explain barriers to customer purchase behavior. In addition, reducing consumers’ risk perception and perfecting the market transaction process with respect to buying behavior should be further studied.

The findings of this review indicate a direct negative relationship between risk perception and customer purchase behavior. To the best of the authors’ knowledge, this review is the first to meta-analytically summarize the impact of risk perception on customer purchase behavior in social sciences research, and it also illuminates new perspectives for future studies.

Since the outbreak of COVID-19, tremendous changes have taken place in the US economy – the economic growth in the whole year of 2020 was negative, and though it enjoyed a significant rebound for the first half of 2021, the growth rate began to decline rapidly by the third quarter, and inflation suddenly rises rapidly, which after came the all-time highs of the “misery index” consisted of the inflation rate and unemployment rate. All signs indicate that the US economy will likely enter a “stagflation” crisis.

This paper analyzes the institutional and social contradictions in the United States during the neoliberal era from the perspectives of domestic social structure of accumulation (SSA) and international SSA based on the SSA theory.

The current risk of stagflation in the US economy is a concentrated outbreak of the long-term accumulated contradictions in neoliberal SSA under the impact of the epidemic, which is the product of the irreconcilable contradictions inherent in the capitalist mode of production.

Based on this analysis, the paper points out that with the deepening of the crisis, the neoliberal SSA is likely to end and a new SSA will be established gradually.

The purpose of this paper is to explore how a perceived ethical climate influences employees’ intention to whistle-blow through internal organizational channels and incorporates the mediating role of organizational identification and moral identity as well as the moderating role of individual risk aversion.

The five proposed hypotheses were tested using hierarchical regression analysis with two waves of data collected in 2016 from 667 employees in Chinese organizations.

The findings indicate that perceived ethical climate had a positive effect on employees’ internal whistle-blowing intention, which was mediated by organizational identification and moral identity. Furthermore, employees’ risk aversion weakened the effect of organizational identification, while the moderating role by moral identity on internal whistle-blowing intention was not validated.

This study explains the psychological mechanism of whistle-blowing intention from the perspective of social identity, which contributes to opening the “black box” of the transmitting processes from the perceived ethical climate to whistle-blowing intention. This study also extends the literature by defining a boundary condition of risk aversion that hinders organizational identification influence on employee whistle-blowing intention.

The purpose of this paper is to design a hybrid robust tracking controller based on an improved radial basis function artificial neural network (IRBFANN) and a novel extended-state observer for a quadrotor system with various model and parametric uncertainties and external disturbances to enhance the resiliency of the control system.

An IRBFANN is introduced as an adaptive compensator tool for model and parametric uncertainties in the control algorithm of non-singular rapid terminal sliding-mode control (NRTSMC). An exact-time extended state observer (ETESO) augmented with NRTSMC is designed to estimate the unknown exogenous disturbances and ensure fast states convergence while overcoming the singularity issue. The novelty of this work lies in the online updating of weight parameters of the RBFANN algorithm by using a new idea of incorporating an exponential sliding-mode effect, which makes a remarkable effort to make the control protocol adaptive to uncertain model parameters. A comparison of the proposed scheme with other conventional schemes shows its much better performance in the presence of parametric uncertainties and exogenous disturbances.

The investigated control strategy presents a robust adaptive law based on IRBFANN with a fast convergence rate and improved estimation accuracy via a novel ETESO.

To enhance the safety level and ensure stable flight operations by the quadrotor in the presence of high-order complex disturbances and uncertain environments, it is imperative to devise a robust control law.

A new idea of incorporating an exponential sliding-mode effect instead of conventional approaches in the algorithm of the RBFANN is used, which makes the control law resistant to model and parametric uncertainties. The ETESO provides rapid and accurate disturbance estimation results and updates the control law to overcome the performance degradation caused by the disturbances. Simulation results depict the effectiveness of the proposed control strategy.

The information used for supervision by regulatory departments in public-private partnership (PPP) projects is primarily transmitted and processed by the PPP implementation department, which negatively impacts the information quality, leading to information asymmetry and undermining the overall effectiveness of supervision. This study aims to explore how to use blockchain to anchor the information used for supervision in PPP projects to the original information, to strengthen the oversight.

This paper adopts the principles of design science research (DSR) to design a conceptual framework that systematically organizes information along the information dissemination chain, ensuring the reliable anchoring of original information. Two-stage interviews involving experts from academia and industry are conducted, serving as formative and summative evaluations to guide the design.

The framework establishes a weak-centralized information organizing mode, including the design of governance community and on-chain and off-chain governance mechanisms. Feedback from experts is collected via interviews and the designed framework is thought to improve information used for supervision. Constructive suggestions are also collected and analyzed for further development.

This paper provides a novel example exploring the inspirations blockchain can bring to project governance, like exercising caution regarding the disorderly expansion of public sector authority in addressing information disadvantages and how to leverage blockchain to achieve this. Technical details conveyed by the framework deepen understanding of how blockchain benefits and the challenges faced in successful implementation for practitioners and policymakers. The targeted evaluation serves as rigorous validation, guiding experts to provide reliable feedback and richer insights by offering them a more cognitively convenient scenario.

The purpose of this paper is to investigate the impact of strategic collaboration (SC) on sustainable supply chain management (SSCM), considering the mediating role of internal knowledge sharing (IKS) and external knowledge sharing (EKS).

The study population consisted of experts associated with the supply chain in the automotive, food, clothing, pharmaceuticals and chemicals industries. After reviewing the literature, a conceptual framework was developed and applied using a structural equation modeling approach. In this study, samples with 271 observations were collected from manufacturing and servicing companies in Iran.

The results showed that SC in the supply chain has a positive impact on the IKS and EKS and SSCM. IKS and EKS have a positive impact on SSCM. Also, the results showed that IKS and EKS fully mediate in the relationship between SC and SSCM.

This study has been done in the context of Iran, so caution should be taken to generalize the results.

The findings of the study contribute to the knowledge of the managers and policy makers in achieving SSCM. The results provide the important environmental and social concepts regarding the sustainability of supply chain using SC and IKS and EKS.