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The purpose of this paper is to design a glass handling robot and conduct a finite element analysis and structural optimization to solve the automation handling problem of large-scale glass production line and aiming at the phenomenon that the vibration of robot manipulator may result in breakage of glass products, especially the fragile chemical or medical glassware. Making modal analysis for the robot is to determine its natural frequencies and vibration modes and lay a foundation for the transient analysis to study the vibration shock response of the robot during its start-up and emergency stop operation.

First, a 3D model of the robot is established according to the requirements of the production field and a finite element model is built on the basis of the 3D model. Then the modal and transient analyses of the robot are carried out according to the fact that the maximum vibration impact of the robot usually appears at the start and emergency stop.

The structure of the robot is improved according to the results of finite element analysis. The dynamic analysis results show that the improved robot’s ability to resist deformation under the impact of vibration shock is enhanced, and the robot can operate smoothly and meet the requirements of design in industrial environments.

The research results avoided the damage caused by the vibration and improved the service life of the robot, providing a foundation for the structural design and mass production of the glass handling robot.

The purpose of this paper is to study the control strategy of transition mode of the stopped-rotor (SR) aircraft under the condition of redundant control and complex aerodynamic characteristics.

This paper first proposes a transition strategy for the conversion between helicopter mode and fixed-wing mode. Then, aiming at the redundancy of the two control systems in the transition process, a control model is proposed, which greatly simplifies the control in conversion mode. Then, to facilitate the design of the control system, the Takagi-Sugeno model of the SR aircraft in transition mode is established. Finally, an explicit model tracking and tuning parameter stability augmentation control system is designed, so that the SR aircraft has a good stability during the transition process. Then, the outer loop control system of transition flight is designed.

The simulation results show that the control strategy proposed in this paper can realize the mode conversion well. It lays a solid foundation for the subsequent engineering flight test for the SR aircraft.

The work done in this paper provides ideas and methods for the flight control system design of SR aircraft in transition mode. The method of designing control model to solve the coordination of redundant control system is also applicable for other multimode aircraft, which provides a simple and convenient method for the multimode aircraft control.

This study explores the connection between big data analytics capabilities and the competitive advantage of the manufacturing sector in Jordan through the mediating role of green radical innovation and green incremental innovation as well as the moderating role of a data-driven culture.

For the purpose of this study, 356 questionnaires were analysed. Convergent validity and discriminant validity tests were performed through structural equation modelling in the Smart-PLS programme, and the data reliability was confirmed. A bootstrapping technique was used to analyse the data. The mediating effect for green radical and green incremental innovation and the moderating effect for data-driven culture were performed.

The empirical results showed that the proposed moderated-mediation model was accepted because the relationships between the constructs were statistically significant. The results of the data analysis supported a positive relationship between big data analytics capabilities and the competitive advantage as well as a mediating effect of green radical innovation and green incremental innovation. It was confirmed that there is a moderating relationship for data-driven culture between green radical innovation, green incremental innovation and competitive advantage.

This cross-sectional study provides a snapshot at a given moment in time, a methodological limitation that affects the generalization of its results, and the results are limited to one country.

This research developed a theoretical model to incorporate big data analytics capabilities, green radical innovation, green incremental innovation, data-driven culture, and competitive advantage. This study provides new findings that bridge the existing research gap in the literature by testing the moderated mediation model with a focus on the organizational benefits of big data analytics capabilities to improve levels of green innovation and competitive advantage in the Jordanian manufacturing sector.

Based on the dynamic capability view, this study aims to draw for the first time the missing link between big data analytics capabilities (BDAC) on both green absorptive capacity (GAC) and green entrepreneurship orientation (GEO). It is theoretically necessary to address how BDAC levels up the GAC to achieve the same level of GEO and then respond to their green business agenda. In addition, the study introduces knowledge sharing (KS) and green organizational ambidexterity (GOA) as potential moderating factors in the relationship between GEO and eco-innovation and explores the mediation role of GAC in the BDAC–GEO relationship.

The study collected 268 questionnaires from employees working in Chinese manufacturing firms using a self-administered survey and cross-sectional research design. The study applied SmartPLS to analyze the obtained data.

The findings revealed that BDAC positively and significantly influences GAC and GEO, positively impacting eco-innovation. The KS and GOA's moderation effect strengthens the relationship between GEO and eco-innovation. GAC partially mediates the relationship between BDAC and GEO.

The study advises firms to invest heavily in developing technological aspects of BDAC as a dynamic strategic capability that facilitates tracking and anticipating the future behavior changes of customers, competitors and market demands. BDAC also allows firms to upgrade and reconfigure their dynamic capabilities by responding to managerial, operational and strategic necessities. BDAC is necessary to increase GAC's impact and help drive GEO's eco-business agenda. Notably, the study gave superior attention to KS and GOA as a backbone of GEO to improve eco-innovation economic and managerial outcomes.

The study highlights the necessity to upgrade and integrate technological aspects of BDAC within firms' GEO to enhance green practices. Significantly, green business practices changed quickly as customers' needs and eco-markets fluctuated; BDAC is the crucial dynamic capability fostering GAC and entrepreneurs' green mindset to deal with environmental challenges. To the best of the author’s knowledge, this study is to predict the potential effect of BDAC on both GAC and GEO. BDAC helps firms to develop GEO eco-business agenda and balance green growth with green issues.

This study investigates the impact of big data analytics capabilities on green supply chain performance. Moreover, it assesses the mediating effect of the green innovation and moderating effect of technological intensity.

This study is based on primary data that were collected from the food and beverages manufacturing sector operating in Jordan. A total of 420 samples were used for the final data analysis. Data analysis was performed via structural equation modeling (SEM) using SmartPLS 3.3.9.

The results of the data analysis supported a positive relationship between big data analytics capabilities and the green supply chain performance as well as a mediating effect of green innovation. It was confirmed that technological intensity moderated the relationship of green innovation on green supply chain performance.

The study faced many limitations such as the method of collecting primary data, which relied on a questionnaire only and the use of cross-sectional data, as well as studying one context and in one country.

The findings can guide managers and policymakers in the Jordanian food and beverage manufacturing sector on how to manage organizational capabilities related to big data analytics to enhance green supply chain performance and improve green innovation in these firms.

This study developed a theoretical and empirical model to investigate the relationship between big data analytics capabilities, green innovation, technological intensity and green supply chain performance. This study offers new theoretical and managerial contributions that add value to the supply chain management and innovation literature by testing the moderated mediation model of these constructs in the food and beverages manufacturing sector in Jordan.

The study explores the potential barriers to data science (DS) implementation in organizations and identifies the key barriers. The identified barriers were explored for their interconnectedness and characteristics. This study aims to help organizations formulate apt DS strategies by providing a close-to-reality DS implementation framework of barriers, in conjunction with extant literature and practitioners' viewpoints.

The authors synthesized 100 distinct barriers through systematic literature review (SLR) under the individual, organizational and governmental taxonomies. In discussions with 48 industry experts through semi-structured interviews, 14 key barriers were identified. The selected barriers were explored for their pair-wise relationships using interpretive structural modeling (ISM) and fuzzy Matriced’ Impacts Croise's Multiplication Appliquée a UN Classement (MICMAC) analyses in formulating the hierarchical framework.

The lack of awareness and data-related challenges are identified as the most prominent barriers, followed by non-alignment with organizational strategy, lack of competency with vendors and premature governmental arrangements, and classified as independent variables. The non-commitment of top-management team (TMT), significant investment costs, lack of swiftness in change management and a low tolerance for complexity and initial failures are recognized as the linkage variables. Employee reluctance, mid-level managerial resistance, a dearth of adequate skills and knowledge and working in silos depend on the rest of the identified barriers. The perceived threat to society is classified as the autonomous variable.

The study augments theoretical understanding from the literature with the practical viewpoints of industry experts in enhancing the knowledge of the DS ecosystem. The research offers organizations a generic framework to combat hindrances to DS initiatives strategically.

This study is the first to examine how big data analytics (BDA) capabilities affect green absorptive capacity (GAC) and green entrepreneurship orientation (GEO). It uses the dynamic capability view, BDA and knowledge-sharing literature. There is a lack of studies addressing the BDA–GAC and BDA–GEO relationships and their potential impact on green innovation. Continuing the ongoing research discussion, a few studies examined the vital implications of knowledge sharing (KS) on GAC, GEO and green innovation.

The study used a cross-sectional and stratified random sampling technique to collect data through self-administered surveys among Chinese manufacturing firm employees. The study applied SmartPLS to analyze the obtained data.

The findings revealed that BDA capabilities positively influence GAC and GEO. In addition, GEO and KS positively impact green innovation. The KS recorded a positive impact on GAC and GEO. Furthermore, GAC and GEO recorded a partial mediating effect.

The study acknowledges that GAC is the backbone of a firm green entrepreneurial orientation, which needs to be aligned with BDA capabilities to anticipate future green business trends. GAC's help drives GEO's green business agenda. KS plays a strategic role in developing GAC, fostering GEO and improving green innovation.

The study highlights the necessity of aligning BDA capabilities to fit firms' GEO green business agendas. This study focuses on the role of BDA capabilities in developing firms' green dynamics capabilities (e.g. GAC), which helps GEO drive superior green business growth. KS develops GAC and boosts GEO to enhance green innovation.