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This chapter analyzes the efficiency levels of a circular economy (CE) with an emphasis on transaction costs. It examines the governance aspect of CE activities in comparison to the predominant linear value creation. Extant CE research in business studies tends to be descriptive and lacks a theoretical foundation, particularly in understanding CE management. Transaction cost theory explains efficiency in economic organizing, lending itself to the study of arrangements that maximize resource efficiency at continued economic virtue. The conceptualization proposes that CE transaction costs are greater than those within the linear economy (LE), primarily due to the uncertainties about reciprocal dependencies, looping material complexities, exchanging novel information, and increased contracting efforts. Geographically bounded and institutionally homogeneous CE initiatives may curb these rising costs. By bringing efficiency concerns into CE analysis, the chapter demonstrates the applicability of transaction cost theory and highlights CE relevance to international business by pointing out spatial choice implications.

Organizational resilience, defined by a firm’s speed in reaching a dynamic equilibrium after a shock and after the shocks are absorbed, and crisis management are critical in a global crisis. The concept of resilience is increasingly used in the economic press; nevertheless, few studies demonstrate empirically how firms became resilient and the lessons to be learned from it. Traditionally, the concept of resilience is approached as resistance in the face of a crisis. The authors go further by showing three-loop learning, which is part of a logic of innovation and regeneration. This study aims to examine how a business can regenerate itself by effectively managing the external threats and disruptions caused by a crisis. Also, this study deepens knowledge on learning process. The double-loop learning process is known in the literature as enabling firms to learn from unexpected events and react accordingly. The findings point out a third loop implying the co-invention of a new business model and a collective mindfulness of changes made.

Using longitudinal data, the authors investigate how the global crisis affects merger negotiations between two companies. This study analyzes the period of dialogue (negotiation) between the two entities with a view to carrying out a merger and then their withdrawal from the project during the pandemic, reshuffling the cards for each company. The negotiation period is not normally disclosed because of its highly confidential and strategic nature and it is therefore difficult for researchers to access merger operations at the negotiation stage. From this viewpoint, this case study was chosen because of the availability of generally inaccessible documentation.

This in-depth case study provides new insights on organizational resilience and the recovery capacity of a firm. The results underline four main triggers that a firm should develop in facing a major crisis: skills; credits; previous and historical relationships; and corporate culture. Recovery capacity depends on reactivity, flexibility, learning and regeneration. Finally, this study points out a three-loop learning experience that can be understood as a learning process in two steps to generate lasting and adaptive changes.

The limitations are those concerning a single case study.

This study highlights the ability to deal with unexpected events. First, this work identifies concrete items that can be perceived by managers as elements enabling a firm to develop resilience. Second, the results show main elements enabling this capacity as reactivity – both companies react quickly and effectively to disturbances to limit the impact on their performance; or flexibility – firms adapt their business model to deal with disruptions. Third, this work underlines a learning capacity process in three steps to recover capacity. This process stimulates creativity and innovation by the teams and stakeholders by placing them at the heart of the change.

This case provides a vivid illustration of firms’ adaptation to a rapidly evolving context because of a global crisis. Theoretical concepts and empirical findings from the literature are combined to present a single consistent picture.

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 purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations.

First, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers’ location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance.

It achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy.

A formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network.

Global value chains (GVCs) have been challenged by several emerging macro-trends during the last years. Among them, sustainability of production and consumption patterns is becoming a central theme given the necessity to mitigate the degradation of the environment and the over-exploitation of scarce natural resources. In this respect, scholars and practitioners increasingly propose the circular economy (CE) approach as a systemic solution to overcome the conventional linear “take–make–use–dispose” model underlying the structure of contemporary global economy. However, the international business (IB) community has introduced the topic of CE only marginally in its debate. The aim of the present study is to fill this research gap identifying the opportunities for integrating IB and CE principles. Thus, the main objective is to investigate whether and how the adoption of the CE paradigm by multinational enterprises (MNEs) may affect activities, geographical configuration, and governance of their relevant GVCs.

The authors address the issue from a conceptual point of view, identifying direct and indirect impacts of CE adoption on GVC, relative enablers, and possible broader implications. Lastly, the authors propose some reflections for future investigations.

The purpose of this paper is to implement a closed loop regulated bidirectional DC to DC converter for an application in the electric power system of more electric aircraft. To provide a consistent power supply to all of the electronic loads in an aircraft at the desired voltage level, good efficiency and desired transient and steady-state response, a smart and affordable DC to DC converter architecture in closed loop mode is being designed and implemented.

The aircraft electric power system (EPS) uses a bidirectional half-bridge DC to DC converter to facilitate the electric power flow from the primary power source – an AC generator installed on the aircraft engine’s shaft – to the load as well as from the secondary power source – a lithium ion battery – to the load. Rechargeable lithium ion batteries are used because they allow the primary power source to continue recharging them whenever the aircraft engine is running smoothly and because, in the event that the aircraft engine becomes overloaded during takeoff or turbulence, the charged secondary power source can step in and supply the load.

A novel nonsingular terminal sliding mode voltage controller based on exponential reaching law is used to keep the load voltage constant under any of the aforementioned circumstances, and its performance is contrasted with a tuned PI controller on the basis of their respective transient and steady-state responses. The former gives a faster and better transient and steady-state response as compared to the latter.

This research gives a novel control scheme for incorporating an auxiliary power source, i.e. rechargeable battery, in more electric aircraft EPS. The battery is so implemented that it can get regeneratively charged when primary power supply is capable of handling an additional load, i.e. the battery. The charging and discharging of the battery is carried out in closed loop mode to ensure constant battery terminal voltage, constant battery current and constant load voltage as per the requirement. A novel sliding mode controller is used to improve transient and steady-state response of the system.

This paper aims to investigate how different knitted structures affect the illuminative effect of polymeric optical fibres (POFs).

Knit prototypes were constructed using a 7-gauge industrial hand flat knitting machine. The textile prototype swatches developed in this study tested POF illumination in three types of knitting structures: intervallic knit and float stitch structures; POF inlaid into double plain and full cardigan structures; and double plain and partial knitting structures. The illuminative effects of the POFs in seven prototype swatches were analysed and compared.

It is possible to use an industrial hand flat knitting machine to knit POFs. Longer floats expose more POFs, which boosts illumination but limits the textile’s horizontal stretchability. The openness of the full cardigan structure maximises POF exposure and contributes to even illumination. The partial knitting in different sections achieves the most complete physical integration of POFs into the knitted textiles but constrains the horizontal stretchability of the textiles.

The integration of POFs into knitted textiles provides a functional illuminative effect. Applications include but are not limited to fashion, architecture and interior design.

This study is novel, as it investigates new POF knitted textiles with different loop structures. This study examines how knit stitches affect POFs in intervallic knit and float stitch, inlaid POF double knit, double plain and partial knit and the illuminative effects of the knitted textile.

This study aims to address the inherent uncertainties within closed-loop supply chain (CLSC) networks through the application of a multi-objective approach, specifically focusing on the optimization of integrated production and transportation processes. The primary purpose is to enhance decision-making in supply chain management by formulating a robust multi-objective model.

In dealing with uncertainty, this study uses Pythagorean fuzzy numbers (PFNs) to effectively represent and quantify uncertainties associated with various parameters within the CLSC network. The proposed model is solved using Pythagorean hesitant fuzzy programming, presenting a comprehensive and innovative methodology designed explicitly for handling uncertainties inherent in CLSC contexts.

The research findings highlight the effectiveness and reliability of the proposed framework for addressing uncertainties within CLSC networks. Through a comparative analysis with other established approaches, the model demonstrates its robustness, showcasing its potential to make informed and resilient decisions in supply chain management.

This study successfully addressed uncertainty in CLSC networks, providing logistics managers with a robust decision-making framework. Emphasizing the importance of PFNs and Pythagorean hesitant fuzzy programming, the research offered practical insights for optimizing transportation routes and resource allocation. Future research could explore dynamic factors in CLSCs, integrate real-time data and leverage emerging technologies for more agile and sustainable supply chain management.

This research contributes significantly to the field by introducing a novel and comprehensive methodology for managing uncertainty in CLSC networks. The adoption of PFNs and Pythagorean hesitant fuzzy programming offers an original and valuable approach to addressing uncertainties, providing practitioners and decision-makers with insights to make informed and resilient decisions in supply chain management.

This study aims to empirically examine the influence of management control systems (MCSs) on knowledge acquisition from innovation failure (KAFIF), which further impacts empowerment, creativity and organizational innovation. This study argues that enabling an MCS positively influences KAFIF, whereas controlling the use of an MCS negatively influences KAFIF. Further, KAFIF positively impacts empowerment, creativity and organizational innovation.

This study aims to create a comprehensive stimulus–organism–response (S-O-R) framework. This framework includes an MCS (belief, interactive, boundary and diagnostic) as a stimulus, KAFIF as an organism and creativity, empowerment and organizational innovation as responses. The data were gathered using an online survey administered to a sample of 321 employees working in India’s micro, small and medium enterprises and analyzed using partial least squares structural equation modeling.

The results indicate that there is no correlation between belief control and the acquisition of knowledge from the failure of innovation, interactive control has a positive association with KAFIF and boundary control has no relationship with KAFIF. Diagnostic control has a significant negative association with KAFIF. Further, this study found that KAFIF positively associates with empowerment, creativity and organizational innovation.

This study is among initial studies that examine the influence of MCSs on KAFIF, which impacts empowerment, creativity and organizational innovation. Further, it helps be one of the initial literature on studying KAFIF rather than innovation success.

In this case study, we examine how a citrus peel valorising company based in the Netherlands was able to adopt a circular business model while navigating regulatory, managerial, and supply chain-related barriers.

In-depth, semi-structured interviews with key personnel in the company, notes from field observations, photographs of the production process, and documents from a legal judgement served as data for this single, qualitative case study. Data were coded inductively using the in vivo technique and were further developed into four themes and a case description.

Results from our study indicate that the regulatory and political contexts in the Netherlands were critical to the company’s success. Like in the case of most fruitful industrial symbioses, partnerships founded on mutual trust and economically appealing value propositions played a crucial role in ensuring commercial viability. Collaborating with larger corporations and maintaining transparent communication with stakeholders were also significant contributing factors. Lastly, employees’ outlook towards circularity combined with their willingness to learn new skills were important driving factors as well.

In addition to expanding the scholarship on the adoption of circular business models, this research offers novel insights to policymakers and practitioners. It provides empirical evidence regarding the importance of public awareness, adaptable legislation, and harmonised policy goals for supporting sustainable entrepreneurship in the circular economy.