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In view of the unknown environmental parameters and uncertain interference during gripping by the manipulator, it is difficult to obtain an effective gripping force with the traditional impedance control method. To avoid this dilemma, the purpose of this study is to propose an adaptive control strategy based on an adaptive neural network and a PID search optimization algorithm for unknown environments.

The method is based on a variable impedance model, and a new impedance model is established using a radial basis function (RBF) neural network to estimate unknown parameters of the impedance model. The approximation errors of the adaptive neural network and the uncertain disturbance are effectively suppressed by designing the adaptive rate. In the meantime, auxiliary variables are constructed for Lyapunov stability analysis and adaptive controller design, and PSA is used to ensure the stability of the adaptive impedance control system. Based on the Lyapunov stability criterion, the adaptive im-pedance control system is proved to have progressive tracking convergence property.

Through comparative simulations and experiments, the superiority of the proposed adaptive control strategy in position and force tracking has been verified. For objects with low flexibility and light-weight (such as a coke, a banana and a nectarine), this control method demonstrates errors of less than 10%.

This paper uses RBF neural networks to estimate unknown parameters of the impedance model in real-time, enhancing system adaptability. Neural network weights are updated online to suppress errors and disturbances. Auxiliary variables are designed for Lyapunov stability analysis. The PSA algorithm is used to adjust controller parameters in real-time. Additionally, comparative simulations and experi-ments are designed to analyze and validate the performance of controller.

This study aims to empirically examine the impact of internal corporate governance mechanisms (ICGM) related to the size of the board, board composition, CEO duality and audit committee independence as a single metric on a firm’s investment decisions.

This study attempts to develop an internal corporate governance quality index comprising 10 items under four main ICGMs – size and independence of the board, CEO duality and audit committee independence – employing panel data analysis to investigate its impact on the investment decisions in 301 nonfinancial firms listed in six emerging capital markets in the Gulf Cooperation Council (GCC) member countries for the years 2015–2020. Data were extracted from sample companies' websites, stock markets, annual reports and Refinitiv database.

This study provides convincing evidence that effective ICGMs minimize inefficient investment and ultimately boost investment efficiency. The findings remain consistent even after considering the potential endogeneity bias.

This study provides empirical evidence on investment efficiency in the GCC region and emphasizes the importance of high-quality ICGMs in reducing inefficient investment. By examining the impact of ICGMs on investment inefficiencies, this study contributes to the corporate governance literature. The GCC region's unique economic and social contexts, with its growing economies, are considered to shed light on this issue.

The lubrication performance of static and dynamic pressure thrust bearings is improved by introducing texture on the sealing edge.

Through model building, meshing and boundary condition setting, the influence of square texture on oil film lubrication performance was simulated and analyzed, and an improved algorithm was applied to perform optimization of lubrication performance.

The findings of this study reveal that the optimum lubrication performance is attained when adjusting the parameters of the square texture to 0.12 mm, 0.1 mm, 1 mm and 34 mm. In such circumstances, the thrust bearing with square textures demonstrates an increase in loading capacity of around 19% and a temperature reduction of about 2ºC compared to a smooth thrust bearing.

The original Reynolds equation is revised, and the influence of square texture on the physical field of oil film is analyzed, considering the turbulence state and cavitation phenomenon. The multi-objective function under square texture parameters was established using BP neural network, and the improved multi-objective salp swarm algorithm was used to optimize the process parameters.

This study explores how chatbot gender and symbolic service recovery may improve the satisfaction of angry customers in the context of service failures. It provides a strategy for companies to deploy chatbots effectively in customer anger.

This research relies upon a systematic literature review to propose three hypotheses, and we recruit 826 participants to examine the effect of chatbot gender on angry customers through one lab study and one field study.

This research shows that female chatbots are more likely to increase the satisfaction of angry customers than male chatbots in service failure scenarios. In addition, symbolic recovery (apology vs. appreciation) moderates the effect of chatbot gender on angry customers. Specifically, male (vs. female) chatbots are more effective in increasing the satisfaction of angry customers when using the apology method, whereas female (vs. male) chatbots are more effective when using the appreciation method.

The rapid advancements in artificial intelligence technology have significantly enhanced the effectiveness of chatbots as virtual agents in the field of interactive marketing. Previous research has concluded that chatbots can reduce negative customer feedback following a service failure. However, these studies have primarily focused on the level of chatbot anthropomorphism and the design of conversational texts, rather than the gender of chatbots. Therefore, this study aims to bridge that gap by examining the effect of chatbot gender on customer feedback, specifically focusing on angry customers following service failures.

Waste generation poses a significant environmental challenge in the United Arab Emirates due to the rapid urbanization, population growth and industrialization witnessed in recent decades. As a result, there has been a substantial surge in waste production. To fulfil its sustainability and circular economy aspirations in various economic domains, the UAE must prioritize efficient waste management. The purpose of this study is to assess the environmental and energy efficiency of the UAE’s economic sectors particularly within its vital energy sectors, which encompass crude oil, natural gas and mining, manufacturing and electricity, by gauging their adherence to sustainability and circularity objectives.

The authors used the data envelopment analysis input–output model to identify sectors that exhibit strong performance as well as those that are falling behind.

Based on this study, the agriculture, the crude oil, natural gas and mining sectors and financial services and banking were found to be the most efficient. The results of this study concluded that the UAE is making progress toward achieving its sustainability and circularity objectives; however, the findings suggest that more effort is needed to fully realize these goals.

By identifying high-performing and underperforming sectors, decision-makers can prioritize efforts to enhance sustainability and circularity in area of greatest need in the economy.

Industrialized construction has brought about expectations of improved productivity in the construction industry. However, the lack of a commonly accepted definition has created confusion regarding the types of development covered by the industrialized construction umbrella. These inconsistent definitions convoluted the discussion on this phenomenon. This study aims to clarify the definition of industrialized construction through a systematic literature review.

This systematic literature review was conducted according to PRISMA principles. Records were gathered from Scopus and Web of Science. Following the scientometric analysis, content analysis was conducted according to the template analysis approach.

The analysis of 121 articles revealed four main themes related to industrialized construction: 1) the construction concept, 2) construction methodologies, 3) systematization, rationalization and automatization and 4) societal and industrial change processes. Definitions of industrialized construction can be analyzed with seven clusters: 1) prefabrication, 2) standardization, 3) sector, 4) integration, 5) manufacturing practices, 6) technological investment and 7) none. Based on the content analysis, the proposed definition is: industrialized construction is the adoption of practices that minimize project-specific work in construction from the start of the design to the end of the building’s life cycle.

This study proposes a definition for industrialized construction following content analysis of broadly sampled literature. The proposed definition can provide a basis on which developments in the construction industry can be reflected.