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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.

Digital transformation is a process in which organizations use technology as an essential resource to improve performance and increase market reach and results.

This research aims to verify how dynamic capabilities are configured for the development of strategies and processes necessary for digital transformation. To this end, qualitative research of an exploratory nature was carried out, operationalized through in-depth individual interviews with a semi-structured approach with managers who occupy leadership positions, in addition to a documentary survey of the internal records of the analyzed organization. In data analysis, the content analysis technique was used.

The main results of the research showed that the dynamic capabilities configured in sensing, seizing and reconfiguring contribute to leveraging digital transformation in the business studied through the reformulation of strategies to integrate and coordinate the implementation of new routines, investments in technological and human resources and actions to change culture with a focus on digital transformation considering the company’s stakeholders.

This transformation affects business models, products, services and processes, as well as the review of strategies, organizational structures and management concepts.

This study aims to investigate the relationships between managers’ cognitive styles, dynamic managerial capabilities and firms’ perceived international performance. The study is based on cognitive-experiential self-theory, dynamic managerial capabilities and international entrepreneurship.

Data were collected from 283 managers of small medium enterprises (SMEs) in Türkiye, an emerging economy. The research was conducted using quantitative methods, and Smart partial least squares (PLS) 4 software was used for data analysis. The data were examined through structural equation modelling and mediation analyses.

Findings indicate that rational cognitive styles positively influence managerial human capital, managerial social capital, managerial cognition and perceived international performance. However, the effect of intuitive cognitive styles was confirmed only on managerial cognition. Additionally, it was found that managerial cognition positively affects perceived international performance, whereas managerial social capital has a negative impact. However, the effects of managerial human capital could not be confirmed. Moreover, a full mediation relationship of managerial cognition between intuitive cognitive styles and perceived international performance was identified.

This research carves out a unique niche by synergizing cognitive-experiential self-theory with dynamic managerial capabilities to investigate their conjoined effect on firms’ international performance, an area previously underexplored. Unveiling insights from burgeoning economies like Türkiye enriches the existing body of knowledge, offering substantial contributions to the field of international business.

Till now no study has been undertaken which test the knowledge management processes for creating dynamic capabilities on the basis of organization structures with interpersonal trust as an important variable. This paper serves as a preliminary study proposing an integrated conceptual model that unmistakably unifies the notions of knowledge management and dynamic capability.

Through an exhaustive literature review, the study explores the role of knowledge management in building dynamic capabilities within the organizations. Through the available literature, authors have attempted to study the relevance of knowledge management against the backdrop of Structuration theory.

Through their proposed framework, authors posit that the structural elements of an organization set the tone for knowledge management within the organization. Organizations face dynamic challenges from the external environment, and in absence of interpersonal trust the creation of dynamic capabilities becomes difficult.

First, the current study enriches the growing research interest in Knowledge management. Second, the study connects Knowledge management and interpersonal trust within the organizations, which in turn is influenced by the structure of the organization. Structures created in the organization decide the direction, quality and quantity of knowledge sharing within the organizations both through social systems and through formal reporting systems. Thus, this paper serves as a preliminary study proposing an integrated conceptual model that unmistakably unifies the notions of knowledge management and dynamic capability.

To provide high torques needed to move a robot’s links, electric actuators are followed by a transmission system with a high transmission rate. For instance, gear ratios of 100:1 are often used in the joints of a robotic manipulator. This results into an actuator with large mechanical impedance (also known as nonback-drivable actuator). This in turn generates high contact forces when collision of the robotic mechanism occur and can cause humans’ injury. Another disadvantage of electric actuators is that they can exhibit overheating when constant torques have to be provided. Comparing to electric actuators, pneumatic actuators have promising properties for robotic applications, due to their low weight, simple mechanical design, low cost and good power-to-weight ratio. Electropneumatically actuated robots usually have better friction properties. Moreover, because of low mechanical impedance, pneumatic robots can provide moderate interaction forces which is important for robotic surgery and rehabilitation tasks. Pneumatic actuators are also well suited for exoskeleton robots. Actuation in exoskeletons should have a fast and accurate response. While electric motors come against high mechanical impedance and the risk of causing injuries, pneumatic actuators exhibit forces and torques which stay within moderate variation ranges. Besides, unlike direct current electric motors, pneumatic actuators have an improved weight-to-power ratio and avoid overheating problems.

The aim of this paper is to analyze a nonlinear optimal control method for electropneumatically actuated robots. A two-link robotic exoskeleton with electropneumatic actuators is considered as a case study. The associated nonlinear and multivariable state-space model is formulated and its differential flatness properties are proven. The dynamic model of the electropneumatic robot is linearized at each sampling instance with the use of first-order Taylor series expansion and through the computation of the associated Jacobian matrices. Within each sampling period, the time-varying linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. An H-infinity controller is designed for the linearized model of the robot aiming at solving the related optimal control problem under model uncertainties and external perturbations. An algebraic Riccati equation is solved at each time-step of the control method to obtain the stabilizing feedback gains of the H-infinity controller. Through Lyapunov stability analysis, it is proven that the robot’s control scheme satisfies the H-infinity tracking performance conditions which indicate the robustness properties of the control method. Moreover, global asymptotic stability is proven for the control loop. The method achieves fast convergence of the robot’s state variables to the associated reference trajectories, and despite strong nonlinearities in the robot’s dynamics, it keeps moderate the variations of the control inputs.

In this paper, a novel solution has been proposed for the nonlinear optimal control problem of robotic exoskeletons with electropneumatic actuators. As a case study, the dynamic model of a two-link lower-limb robotic exoskeleton with electropneumatic actuators has been considered. The dynamic model of this robotic system undergoes first approximate linearization at each iteration of the control algorithm around a temporary operating point. Within each sampling period, this linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. The linearization process relies on first-order Taylor series expansion and on the computation of the associated Jacobian matrices. The modeling error which is due to the truncation of higher-order terms from the Taylor series is considered to be a perturbation which is asymptotically compensated by the robustness of the control algorithm. To stabilize the dynamics of the electropneumatically actuated robot and to achieve precise tracking of reference setpoints, an H-infinity (optimal) feedback controller is designed. Actually, the proposed H-infinity controller for the model of the two-link electropneumatically actuated exoskeleton achieves the solution of the associated optimal control problem under model uncertainty and external disturbances. This controller implements a min-max differential game taking place between: (i) the control inputs which try to minimize a cost function which comprises a quadratic term of the state vector’s tracking error and (ii) the model uncertainty and perturbation inputs which try to maximize this cost function. To select the stabilizing feedback gains of this H-infinity controller, an algebraic Riccati equation is being repetitively solved at each time-step of the control method. The global stability properties of the H-infinity control scheme are proven through Lyapunov analysis.

Pneumatic actuators are characterized by high nonlinearities which are due to air compressibility, thermodynamics and valves behavior and thus pneumatic robots require elaborated nonlinear control schemes to ensure their fast and precise positioning. Among the control methods which have been applied to pneumatic robots, one can distinguish differential geometric approaches (Lie algebra-based control, differential flatness theory-based control, nonlinear model predictive control [NMPC], sliding-mode control, backstepping control and multiple models-based fuzzy control). Treating nonlinearities and fault tolerance issues in the control problem of robotic manipulators with electropneumatic actuators has been a nontrivial task.

The novelty of the proposed control method is outlined as follows: preceding results on the use of H-infinity control to nonlinear dynamical systems were limited to the case of affine-in-the-input systems with drift-only dynamics. These results considered that the control inputs gain matrix is not dependent on the values of the system’s state vector. Moreover, in these approaches the linearization was performed around points of the desirable trajectory, whereas in the present paper’s control method the linearization points are related with the value of the state vector at each sampling instance as well as with the last sampled value of the control inputs vector. The Riccati equation which has been proposed for computing the feedback gains of the controller is novel, so is the presented global stability proof through Lyapunov analysis. This paper’s scientific contribution is summarized as follows: (i) the presented nonlinear optimal control method has improved or equally satisfactory performance when compared against other nonlinear control schemes that one can consider for the dynamic model of robots with electropneumatic actuators (such as Lie algebra-based control, differential flatness theory-based control, nonlinear model-based predictive control, sliding-mode control and backstepping control), (ii) it achieves fast and accurate tracking of all reference setpoints, (iii) despite strong nonlinearities in the dynamic model of the robot, it keeps moderate the variations of the control inputs and (iv) unlike the aforementioned alternative control approaches, this paper’s method is the only one that achieves solution of the optimal control problem for electropneumatic robots.

The use of electropneumatic actuation in robots exhibits certain advantages. These can be the improved weight-to-power ratio, the lower mechanical impedance and the avoidance of overheating. At the same time, precise positioning and accurate execution of tasks by electropneumatic robots requires the application of elaborated nonlinear control methods. In this paper, a new nonlinear optimal control method has been developed for electropneumatically actuated robots and has been specifically applied to the dynamic model of a two-link robotic exoskeleton. The benefit from using this paper’s results in industrial and biomedical applications is apparent.

A comparison of the proposed nonlinear optimal (H-infinity) control method against other linear and nonlinear control schemes for electropneumatically actuated robots shows the following: (1) Unlike global linearization-based control approaches, such as Lie algebra-based control and differential flatness theory-based control, the optimal control approach does not rely on complicated transformations (diffeomorphisms) of the system’s state variables. Besides, the computed control inputs are applied directly on the initial nonlinear model of the electropneumatic robot and not on its linearized equivalent. The inverse transformations which are met in global linearization-based control are avoided and consequently one does not come against the related singularity problems. (2) Unlike model predictive control (MPC) and NMPC, the proposed control method is of proven global stability. It is known that MPC is a linear control approach that if applied to the nonlinear dynamics of the electropneumatic robot, the stability of the control loop will be lost. Besides, in NMPC the convergence of its iterative search for an optimum depends on initialization and parameter values selection and consequently the global stability of this control method cannot be always assured. (3) Unlike sliding-mode control and backstepping control, the proposed optimal control method does not require the state-space description of the system to be found in a specific form. About sliding-mode control, it is known that when the controlled system is not found in the input-output linearized form the definition of the sliding surface can be an intuitive procedure. About backstepping control, it is known that it cannot be directly applied to a dynamical system if the related state-space model is not found in the triangular (backstepping integral) form. (4) Unlike PID control, the proposed nonlinear optimal control method is of proven global stability, the selection of the controller’s parameters does not rely on a heuristic tuning procedure, and the stability of the control loop is assured in the case of changes of operating points. (5) Unlike multiple local models-based control, the nonlinear optimal control method uses only one linearization point and needs the solution of only one Riccati equation so as to compute the stabilizing feedback gains of the controller. Consequently, in terms of computation load the proposed control method for the electropneumatic actuator’s dynamics is much more efficient.

The lightweight design of aircraft seats can significantly improve fuel efficiency and reduce greenhouse gas emissions. Metal additive manufacturing (MAM) can produce lightweight topology-optimized designs with improved performance, but limited build volume restricts the printing of large components. The purpose of this paper is to design a lightweight aircraft seat leg structure using topology optimization (TO) and MAM with build volume restrictions, while satisfying structural airworthiness certification requirements.

TO was used to determine a lightweight conceptual design for the seat leg structure. The conceptual design was decomposed to meet the machine build volume, a detailed CAD assembly was designed and print orientation was selected for each component. Static and dynamic verification was performed, the design was updated to meet the structural requirements and a prototype was manufactured.

The final topology-optimized seat leg structure was decomposed into three parts, yielding a 57% reduction in the number of parts compared to a reference design. In addition, the design achieved an 8.5% mass reduction while satisfying structural requirements for airworthiness certification.

To the best of the authors’ knowledge, this study is the first paper to design an aircraft seat leg structure manufactured with MAM using a rigorous TO approach. The resultant design reduces mass and part count compared to a reference design and is verified with respect to real-world aircraft certification requirements.

This article introduces the special issue of Learning and Development in Highly-Dynamic VUCA Contexts. The issue reviews the concept of VUCA (volatility, uncertainty, complexity and ambiguity), highlights its implications for the learning and development function and argues that learning and development play a critical role in helping organisations, people and the societal context in which they operate to work within and navigate VUCA contexts.

The contributions to this special issue propose a novel learning and development framework that will inform L&D as the provision of training, learning and development activities in organisations within highly dynamic VUCA contexts and ensuring a strong external focus including organisational, people, community, economic and societal sustainability.

We, the authors, propose seven features of a strategic sustainability L&D function and L&D professional role that are a fit with highly dynamic VUCA contexts.

The proposed framework has important implications for the way in which L&D is structured, its key priorities and plans and the competencies of L&D professionals to add value to all stakeholders. We also emphasise that the work on the L&D function in highly dynamic VUCA contexts needs to be broader and move beyond a performance orientation.

The proposed strategic sustainability role for the L&D function expands theoretically our understanding of how L&D can have impacts at the nexus of the organisation and highly dynamic VUCA contexts, in addition to broadening the constellation of stakeholders that it potentially enhances.

Information and communication technologies (ICTs) enable firms to improve their processes to remain competitive and profitable in today’s market. These demands not only value economic results but also social impact and environmental care. In other words, firms must achieve sustainable performance. However, to take on these new sustainability challenges, firms must have dynamic capabilities to take advantage of highly changing technology. Thus, this study aims to examine the mediating role of dynamic capabilities in the relationship between ICT and sustainable performance.

This study was empirical, associative and explanatory, following a latent variable design. The sample of the study consisted of partners, founders, executives and promoters from 102 Colombian new technology-based firms selected through purposive non-probabilistic sampling. Variance-based structural equation modeling or partial least squares was used for the statistical data analysis.

A higher-order model was tested, corroborating that ICT was composed of two dimensions (use and acquisition), dynamic capabilities were composed of three dimensions (absorption, innovation and adaptation), while sustainable performance showed a unidimensional structure. As for the research hypotheses, all the direct effects were supported, as well as the mediating effect of dynamic capability in the relationship between ICT and sustainable performance, this being a complementary mediation.

This study highlights the importance of dynamic capabilities for firms today, especially those working with high levels of technology. Also, considering the results obtained, firms must implement better strategies in the acquisition and use of technology to improve their sustainable performance in dynamic and uncertain environments.

This paper aims to develop an algorithm to study the impact of dynamic resource disruption on project makespan and provide a suitable resource disruption ratio for various complex industrial and emergency projects.

This paper addresses the RCPSP in dynamic environments, which assumes resources will be disrupted randomly, that is, the information about resource disruption is not known in advance. To this end, a reactive scheduling model is proposed for the case of random dynamic disruptions of resources. To solve the reactive scheduling model, a hybrid genetic algorithm with a variable neighborhood search is proposed.

The results obtained on the PSLIB instances prove the performance advantage of the algorithm; through sensitivity analysis, it can be obtained, the project makespan increases exponentially as the number of disruptions increase. Furthermore, if more than 50% of the project's resources are randomly disrupted, the project makespan will be significantly impacted.

The paper focuses on the impact of dynamic resource disruptions on project makespan. Few studies have considered stochastic, dynamic resource uncertainty. In addition, this research proposes a reasonable scheduling algorithm for the research problem, and the conclusions drawn from the research provide decision support for project managers.

This study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.

A two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.

On average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.

This study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.