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This paper aims to consider the enabling and coercive features of formal control in non-hierarchical settings and the factors influencing perceptions of controls.

This paper is a qualitative case study of a single organization. Data are collected via semi-structured interviews, a range of published materials and a management presentation. Analysis considered the features of coercive and enabling control at the level of individual controls.

In this highly decentralized organization, internal and global transparency predominate and help managers respond to contingencies in flexible ways. Managers cannot repair certain elements of controls to ensure there is stability in an otherwise flexible system. The existence (absence) of enabling features combined with the type of controls (e.g. action or results controls) lacking enabling features influence managers’ perceptions of control.

Few studies have considered formal controls in non-hierarchical organizations. The findings reveal the importance of minimally coercive control features in creating a stable structure for controlling performance. The findings may not be relevant to other hierarchical organizations.

The study is conducted in a highly decentralized context where managers have extensive autonomy (flexibility). The context allows the role of minimally coercive control features to be explored in an essentially enabling organizational setting.

Path planning in unknown or partly unknown environment is a quite complex task, partly because it is an evolving globally optimal path affected by the motion of the robot and the changing of environmental information. The purpose of this paper is to propose an online path planning approach for a mobile robot, which aims to provide a better adaptability to the motion of the robot and the changing of environmental information.

This approach treats the globally optimal path as a changing state and estimates it online with two steps: prediction step, which predicts the globally optimal path based on the motion of the robot; and updating step, which uses the up‐to‐date environmental information to refine the prediction.

Simulations and experiments show that this approach needs less time to reach the destination than some classical algorithms, provides speedy convergence and can adapt to unexpected obstacles or very limited prior environmental information. The better performances of this approach have been proved in both field and indoor environments.

Compared with previous works, the paper's approach has three main contributions. First, it can reduce the time consumed in reaching the destination by adopting an online path planning strategy. Second, it can be applied in such environments as those with unexpected obstacles or with only limited prior environmental information. Third, both motion error of the robot and the changing of environmental information are considered, so that the global adaptability to them is improved.

Digital entrepreneurship is the key to economic survival and the lantern of jobs in developing countries. The debate about the challenges facing early digital entrepreneurs (DEs) in developing countries is still ambiguous. This study attempts to fulfill the gap with an in-depth examination of Jordan.

Referring to a digital start-up database hosted by the Ministry of Digital Economy and Entrepreneurship in Jordan, the study interviews a random sample of (n = 45) early (less than one-year seniority) DEs. Thematic analysis is carried out facilitated by NVivo 20 software. E-Commerce, agriculture technology, data and artificial intelligence and entertainment were at the top of the interviewed start-ups.

Nine challenges were observed, critically analyzed and discussed. The challenges are (1) the lack of realistic funding in terms and guarantees; (2) the negligence of guidance and advisory of incubators and entrepreneurship centres; (3) the emergence of unexpected risks; (4) the stringent economic situation; (5) competition; (6) legal and legislative obstacles; (7) obstacles to accessing markets; (8) team management and finally (9) disorganization in the entrepreneurial environment. The study sets recommendations to support early DEs in their journey.

This study highlights the significant implications for aspiring DEs by focusing on some challenges that might face their start-ups such as institutional, technology and local dimensions of context and measures to develop the entrepreneurial and digital competencies. This includes sustainable funding, poor direct guidance and advisory, unexpected failures/risks, and economic obstacles. This study might be considered a road map for the decision-makers to build their strategies for eliminating the main barriers for early DEs and start-ups.

Although recent literature discussed the challenges of entrepreneurs in Jordan, this is the first that identifies early DEs’ challenges and uses 45% samples of the community.

Autonomous obstacle avoidance is important in unmanned surface vehicle (USV) navigation. Although the result of obstacle detection is often inaccurate because of the inherent errors of LIDAR, conventional methods typically emphasize on a single obstacle-avoidance algorithm and neglect the limitation of sensors and safety in a local region. Conventional methods also fail in seamlessly integrating local and global obstacle avoidance algorithms. This paper aims to present a cooperative manoeuvring approach including both local and global obstacle avoidance.

The global algorithm used in our USV is the Artificial Potential Field-Ant Colony Optimization (APF-ACO) obstacle-avoidance algorithm, which plans a relative optimal path on the specified electronic map before the cruise of USV. The local algorithm is a multi-layer obstacle-avoidance framework based on a single LIDAR to present an efficient solution to USV path planning in the case of sensor errors and collision risks. When obstacles are within a layer, the USV uses a corresponding obstacle-avoidance algorithm. Then the USV moves towards the global direction according to fuzzy rules in the fuzzy layer.

The presented method offers a solution for obstacle avoidance in a complex environment. The USV follows the global trajectory planed by the APF-ACO algorithm. While, the USV can bypass current obstacle in the local region based on the multi-layer method effectively. This fact was validated by simulations and field trials.

The method presented in this paper takes advantage of algorithm integration that remedies errors of obstacle detection. Simulation and experiments were also conducted for performance evaluation.

The purpose of the paper is to classify the full scope of hazards in the way to effective project‐ and decision‐management in teams, and to present team leaders with a practical set of guidelines for coping with those obstacles, towards successful achievements.

The paper provides a classification of the full spectrum of possible factors responsible for mishaps, faults and failures which regularly tend to occur within managerial and organizational activities at all levels. It goes on to present a set of two tools that, jointly applied, can provide managers with the necessary control to lead more team processes and projects towards successful terminations: the “revised decision square model” and the “capi” model.

The paper provides evidence in the form of quotes from testimonies of managers who have adopted the proposed strategy for their every‐day use within their teams.

The paper offers a practical step‐by‐step set of guidelines to lead managers towards a relatively high level of control in the management of effective and efficient team decision making and implementation processes, ensuring their route towards successful achievements.

Limited attention has been given in the literature to the studying of practical and applicable managerial techniques to successful decision‐implementation in teams. This paper focuses on this neglected domain, proposing a solution, in the form of an integrative strategy.

The paper aims to describe the design and development of an automated guided vehicle (AGV) that incorporates artificial intelligence techniques to increase its autonomy and flexibility. The aim is developing a flexible AGV that operates as a flexible material handling system (MHS) in dynamic industrial environments.

Introduces the entire on‐board control system including hardware and software designs. The sensory system consists of a laser navigation system for localisation and a security laser scanner for sensing the environment. The software architecture is instantiated in a CPU that is connected to low level controllers through a CAN bus. Simplicity, flexibility, robustness and safety were concerned in the design process.

The developed prototype is able to operate in partially structured and dynamic environments, is easily configured using an approximated description of the workplace and is able to adapt when slight floor layout modifications. This development shows that current technology permits introducing intelligent vehicles in complex manufacturing systems.

The prototype is successfully tested in a real factory, operating as a flexible MHS, transporting pallets between production and storage lines.

A novel flexible AGV is designed and developed to operate as a flexible MHS in dynamic industrial environments. The system satisfies the safety and robustness requirements of industrial applications. The flexible MHS results especially suitable for manufacturing systems that suffers from cyclic and seasonal variations and for flexible manufacturing systems where the possibility of choosing alternative routes is a must.

In this paper, a new cooperation control scheme for multiple robot material handling is presented. First, the event‐based planning and control method is introduced, which lays down the foundation for sensor‐referenced cooperation of multiple robot systems. The key step is the development of event‐based action reference. Based on the real‐time sensory information, the event‐based action reference drives the system to achieve the best possible coordination. The event‐based cooperation control scheme can easily be implemented in a distributed computer system. A real‐time control and computing architecture is proposed to implement this scheme in a parallel computation. The new multiple robot cooperation scheme has been experimentally implemented and tested on two 6‐DOF PUMA 560 robots. The experimental results have demonstrated the advantages of the scheme.

Accessibility is now a major issue in the design and maintenance of housing estates. This paper considers the reasons why this issue has emerged and the main obstacles to accessibility encountered by housing estate residents. Focusing on a mature estate in South Belfast, Northern Ireland, investigates the obstacles to accessibility experienced by the residents in order to produce a hierarchy of impacts. Residents were surveyed on a number of issues including location, roads and pavements, transportation, level change, wayfinding, safety and security, and public areas. It was discovered that obstacles relating to wayfinding created the greatest problems for residents; however, attitudes towards accessibility varied according to the age of the respondent. The study concludes that accessibility should be introduced estate‐by‐estate dependent on a resident profile in order to maximise resources and advocates the adoption of a co‐ordinated interagency approach.