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The food industry is continuously developing its online services called food delivery applications (FDAs). This study aims to evaluate FDA's importance–performance and identify strategies to maximize its potential gains from a business partner's perspective.

Data are collected from 208 FDA partners in Indonesia. Importance–performance analysis (IPA) is applied to evaluate the FDA feature and extended the theory of potential gain in customer value (PGCV) to achieve potential gains from FDA business partners.

This study provides a clear and measurable direction for future research to develop FDA performance. Owning customer data, revenue sharing and competitive advantage are the most potential gains from joining the FDA from the business partner perspective.

The respondents are restaurants from the micro, small, and medium enterprises levels. Further research should involve middle to upper level restaurants to discover all business partners' perceptions. This will be very helpful for FDA providers interested in improving the best performance for all their partners.

FDA providers must focus on improving and maintaining the features of owning customer data, revenue sharing, competitive advantage, stable terms and conditions, customer interface, building customer loyalty, online presence, user credit rating, promotion and offers, delivery service and sales enhancement to increase consumer satisfaction and meet the expectations desired by business partners.

This research provides a meaningful theoretical foundation for future work. It extends the theory of PGCV using the value of a partner perspective as a substitute for customer value; hence, the authors call it a potential gain in partner value.

Grounded in dynamic capabilities theory, this study aims to examine how dynamic capabilities and a transactive memory system (TMS) can build the resilience of service organizations and improve their financial performance. Limited studies examine the link between a TMS and organizational resilience.

The authors test a theoretical model on a sample of 350 UK service firms that were impacted by the COVID-19 pandemic and analyze the data using partial least square structural equation modeling.

Results highlight the positive effects of a TMS and dynamic capabilities on organizational resilience. Only a TMS and organizational resilience have direct positive effects on financial performance.

To the best of the authors’ knowledge, this is the first study to ascertain the influence of a TMS on organizational resilience in service firms following adversity.

The operational framework of external financing in the correlation between the gender of entrepreneurs and firm performance remains to be resolved. This study aims to investigate the mediating effect of external financing on gender-based disparities in private firm performance and to explore its heterogeneity within the Chinese context.

Based on national data from the 10th to 13th Chinese Private Enterprise Survey, this study used a bootstrap-based mediation effect model to analyze the role of external financing as a mediator in the relationship between entrepreneur gender and firm performance.

This study found that external financing is a constructive mediator between entrepreneur gender and firm performance. Heterogeneity analysis revealed that external financing plays a complementary mediation role in the impact of entrepreneur gender on performance in West China. In the tertiary industry, external financing acts as the sole mediator for the impact of gender on firm performance. Notably, this mediating effect is present in non-startups but not in startups.

The findings suggest that external financing can improve the firm performance of female entrepreneurs. Governments and policymakers should strengthen financial support for female entrepreneurs in West China, tertiary industry and non-startup enterprises.

This paper contributes to the literature on gender and corporate governance by shedding light on the mediating role of external financing in the relationship between the gender of business owners and firm performance.

This study aims to investigate the direct effect of intellectual capital on the organizational performance of Indonesian state-owned enterprises (SOEs) and their subsidiaries. Furthermore, it also examines whether the relationship is mediated by open innovation and moderated by organizational inertia.

This study is designed as quantitative research. A survey method is employed to collect data by distributing questionnaires to the upper-level managers of the SOEs and their subsidiaries. A total of 293 questionnaires were distributed to the respondents, and 97 responses were obtained for further analysis. The partial least square structural equation modeling (PLS-SEM) is used to test the hypotheses. A mediation-moderation research framework is employed.

The results show that intellectual capital has a positive effect on organizational performance. Further results also demonstrate that open innovation mediates the intellectual capital–organizational performance relationship and organizational inertia moderates the intellectual capital–organizational performance relationship. Theoretically, the findings contribute to the resource-based view (RBV) and knowledge-based view (KBV) by providing empirical evidence of the importance of distinctive internal resources in achieving superior organizational performance. Practically, the findings provide strategic information for managers that they should properly manage intellectual capital, open innovation and organizational inertia because of their effects on organizational performance.

First, this study addresses the previous research gaps by confirming that intellectual capital has a positive effect on organizational performance in the research setting of an emerging market. Second, by using a mediation research framework, this study shows that open innovation mediates the relationship between intellectual capital and organizational performance. Third, by using a moderating research framework, this study also reveals that organizational inertia weakens the relationship between intellectual capital and organizational performance. Those associations are rarely researched.

This study aims to explore the relationship between firm risk, capital structure, cost of equity capital and social and environmental sustainability during the COVID-19 pandemic for companies listed on Tehran Stock Exchange.

To this aim, the information about 190 companies in 2014–2020 was retrieved to be analyzed. The total risk and systematic risk were used as the indicators of company risk; the industry-adjusted earnings price ratio (IndEP) and GORDON were used for the cost of equity capital. To measure social sustainability and environmental sustainability, the procedure suggested by Arianpoor and Salehi (2020) was used.

Underleveraged firms have had a lower total risk during the COVID-19 pandemic, while overleveraged firms have not had a higher risk during this time. In overleveraged firms, using systematic risk has a negative impact on social sustainability during the COVID-19 pandemic. In overleveraged firms, using total risk and systematic risk has a significant negative impact on environmental sustainability in the pandemic. Besides, overleveraged firms have a lower cost of equity capital (IndEP) during COVID-19.

To the best of the authors’ knowledge, no similar study has so far examined the joint impact of COVID-19 and corporate risk on social and environmental sustainability and also the joint impact of COVID-19 and capital structure on the cost of equity. This study contributes to the related literature by providing corporations with insightful post-pandemic directions on capital structure decisions and social and environmental activities. Furthermore, this research and the relevant findings can help understand and develop social responsibility in Iran as a developing country.

Limited by the types of sensors, the state information available for musculoskeletal robots with highly redundant, nonlinear muscles is often incomplete, which makes the control face a bottleneck problem. The aim of this paper is to design a method to improve the motion performance of musculoskeletal robots in partially observable scenarios, and to leverage the ontology knowledge to enhance the algorithm’s adaptability to musculoskeletal robots that have undergone changes.

A memory and attention-based reinforcement learning method is proposed for musculoskeletal robots with prior knowledge of muscle synergies. First, to deal with partially observed states available to musculoskeletal robots, a memory and attention-based network architecture is proposed for inferring more sufficient and intrinsic states. Second, inspired by muscle synergy hypothesis in neuroscience, prior knowledge of a musculoskeletal robot’s muscle synergies is embedded in network structure and reward shaping.

Based on systematic validation, it is found that the proposed method demonstrates superiority over the traditional twin delayed deep deterministic policy gradients (TD3) algorithm. A musculoskeletal robot with highly redundant, nonlinear muscles is adopted to implement goal-directed tasks. In the case of 21-dimensional states, the learning efficiency and accuracy are significantly improved compared with the traditional TD3 algorithm; in the case of 13-dimensional states without velocities and information from the end effector, the traditional TD3 is unable to complete the reaching tasks, while the proposed method breaks through this bottleneck problem.

In this paper, a novel memory and attention-based reinforcement learning method with prior knowledge of muscle synergies is proposed for musculoskeletal robots to deal with partially observable scenarios. Compared with the existing methods, the proposed method effectively improves the performance. Furthermore, this paper promotes the fusion of neuroscience and robotics.

Sharing project information is critical for the success of medical crowdfunding campaigns. However, few users share medical crowdfunding projects on their social networks, and the sharing behavior of medical crowdfunding projects on social networking sites has not been well studied. Therefore, this study explored the factors and potential mechanisms influencing users’ sharing behaviors on networking sites.

A research model was developed based on the attribution-affect model of helping and social capital theory. Data were collected using a longitudinal survey. Partial least squares structural equation modeling was used to analyze the collected data. We conducted post hoc analyses to validate the results of the quantitative analysis.

The analysis results verified the effects of perceived external attribution, perceived uncontrollable attributions, and perceived unstable attributions on sympathy and identified the effect of sympathy and social characteristics of medical crowdfunding users on sharing behavior.

This research provides a comprehensive theoretical understanding of users’ sharing behavior characteristics and provides implications for enhancing the efficiency of medical crowdfunding activities.

The purpose of this paper aims to investigate the adaptive impedance control and its optimized PSO algorithm for force tracking of a dual-arm cooperative robot. Because the dual-arm robot is directly in contact with external environment, controlling the mutual force between robot and external environment is of great importance. Besides, a high compliance of the robot should be guaranteed.

An impedance control based on Particle Swarm Optimization (PSO) algorithm is designed to track the mutual force and achieve compliance control of the robot end.

The experimental results show that the impedance control coefficients can be automatically tuned converged by PSO algorithm.

The system can reach a steady state within 0.03 s with overshoot convergence, and the force fluctuation range at the steady state decreases to about ±0.08 N even under the force mutation condition.

The global emphasis on sustainability is driving organizations to embrace financial technology (Fintech) solutions as a means of enhancing their sustainable performance. This study seeks to unveil the intermediary role played by green finance and competitiveness, along with the moderating impact of digital transformation (DT), in the intricate relationship between Fintech adoption and sustainable performance.

Drawing on existing literature, we construct a comprehensive conceptual framework to thoroughly analyse these interconnected variables. To empirical validate of our model, a dual structural equation modelling–artificial neural network) SEM–ANN approach was employed, adding a robust layer of validation to our study’s proposed framework. A sample of 438 banking employees in Pakistan was collected using a simple random sampling technique, with 411 samples deemed suitable for subsequent analysis. Initially, data scrutiny and hypothesis testing were carried out using Smart-PLS 4.0 and SPSS-23. Subsequently, the ANN technique was utilized to assess the importance of exogenous factors in forecasting endogenous factors.

The findings from this research underscore the direct and significant influence of Fintech adoption and DT on the sustainable performance of banks. Notably, green finance and competitiveness emerge as pivotal mediators, bridging the gap between Fintech adoption and sustainable performance. Moreover, DT emerges as a critical moderator, shaping the relationships between Fintech adoption and both green finance and competitiveness. The integration of the ANN approach enhances the SEM analysis, providing deeper insights and a more comprehensive understanding of the subject matter.

This study contributes to the enhanced comprehension of Fintech, green finance, competitiveness, DT and the sustainable performance of banks. Recognizing the importance of amalgamating Fintech adoption, green finance and transformational leadership becomes essential for elevating the sustainable performance of banks. The insights garnered from this study hold valuable implications for policymakers, practitioners and scholars aiming to enhance the sustainable performance of banks within the competitive business landscape.

Component positioning is an important part of aircraft assembly, aiming at the problem that it is difficult to accurately fall into the corresponding ball socket for the ball head connected with aircraft component. This study aims to propose a ball head adaptive positioning method based on impedance control.

First, a target impedance model for ball head positioning is constructed, and a reference positioning trajectory is generated online based on the contact force between the ball head and the ball socket. Second, the target impedance parameters were optimized based on the artificial fish swarm algorithm. Third, to improve the robustness of the impedance controller in unknown environments, a controller is designed based on model reference adaptive control (MRAC) theory and an adaptive impedance control model is built in the Simulink environment. Finally, a series of ball head positioning experiments are carried out.

During the positioning of the ball head, the contact force between the ball head and the ball socket is maintained at a low level. After the positioning, the horizontal contact force between the ball head and the socket is less than 2 N. When the position of the contact environment has the same change during ball head positioning, the contact force between the ball head and the ball socket under standard impedance control will increase to 44 N, while the contact force of the ball head and the ball socket under adaptive impedance control will only increase to 19 N.

In this paper, impedance control is used to decouple the force-position relationship of the ball head during positioning, which makes the entire process of ball head positioning complete under low stress conditions. At the same time, by constructing an adaptive impedance controller based on MRAC, the robustness of the positioning system under changes in the contact environment position is greatly improved.