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Narrow, managerially centered notions of organizational culture remain hegemonic, marginalizing richer, anthropological approaches as well as efforts to understand how the beliefs and practices of organizations are fundamentally shaped by the wider societal dynamics within which they are embedded. In this paper, the authors draw upon recent efforts to explore the interface of scholarship on practice and the institutional logics perspective to highlight the utility of a practice-driven institutional approach to the study of organizational culture that brings society back in. Empirically, the authors present a longitudinal case study of a Chinese private enterprise, and analyze how the unfolding dynamics of a strong community logic increasingly affected by a rising market logic, shaped the formation of political coalitions internally and externally as organizational members aimed to maintain truces between the push and pull of logics over a period of 22 years. Through an analysis of seven episodes that we conceptualize as “cultural encounters,” the authors find that a combination of compartmentalization and overall integration of logics contributes to provisional truces, and that people in the same cohort who share common geographic socialization are more likely to form allies. Our aim is to encourage future scholars to study how societal beliefs and practices work their way into organizations in a variety of explicit as well as more mundane, hidden ways.

The purpose of this paper is to examine a new insurance policy against natural disasters.

The authors propose an optimisation model, which involves both the insurer and the farmer. The farmer decides to insure his farm if and only if insurance improves the utility he is expecting over a given year. Therefore, the paper takes the perspective of an insurer who wants to maximise the farmer's wealth, so that he will be more likely to subscribe the policy. The choice and combination of the policies are then determined and designed by the insurer to reach that aim.

The paper proves that the market for insurance could grow with a combination of participating contracts and market‐based instruments. The first cover individual risks while the second cover systematic risks.

The new policy leads both the insurer to manage small and large risks and the insured to be financially interested. It also provides an optimal coverage against natural events for insured farmers.

The paper offers many perspectives for the renewal of the crop insurance market using new instruments.

Certain general principles of regulation and control are developed and substantiated by means of evidence from a variety of fields. First, success in regulation is a function of several variables including adaptability, use of heuristic devices, system structure and characteristics of its constituent parts. Second, both internal specialization of a system and the variety of its dependencies on the environment are important. However, while the variety is important only in the short‐run, system structure is important both in the short‐run and the long‐run. Third, according to the contemporary cybernetic paradigm, a self‐regulatory system must be an open system. This is concluded to be a myth. The theory is developed and illustrated.

In order to solve the current imbalance of academic resources within the discipline, this article builds a three-dimensional talent evaluation model based on the topic–author–citation based on the z index and proposes the ZAS index to evaluate scholars on different research topics within the discipline.

Based on the sample data of the CSSCI journals in the discipline of physical education in the past five years, the keywords were classified into 13 categories of research topics including female sports. The ZAS index of scholars on topic of female sports and so on was calculated, and quantitative indexes such as h index p index and z index were calculated. Comparative analysis of the evaluation effect was performed.

It is found that compared with the h index and p index, the z index achieves a better balance between the quantity, quality and citation distribution of scholars' results and effectively recognizes that the citation quality is higher and the number of citations of each paper is more balanced. In addition, compared to the z index, this article is based on a ZAS index model with an improved three-dimensional topic–author–citation relationship in research fields such as female sports.

It can identify some outstanding scholars who are engaged in small-scale or emerging topic research such as female sports and are excellent in different research areas. Talents create an objective and fair evaluation environment. At the same time, the ranking ability of ZAS indicators in the evaluation of talents is the strongest, and it is expected to be used in practical evaluations.

This paper aims to study the application of reinforcement learning (RL) in the control of an output-constrained flapping-wing micro aerial vehicle (FWMAV) with system uncertainty.

A six-degrees-of-freedom hummingbird model is used without consideration of the inertial effects of the wings. A RL algorithm based on actor–critic framework is applied, which consists of an actor network with unknown policy gradient and a critic network with unknown value function. Considering the good performance of neural network (NN) in fitting nonlinearity and its optimum characteristics, an actor–critic NN optimization algorithm is designed, in which the actor and critic NNs are used to generate a policy and approximate the cost functions, respectively. In addition, to ensure the safe and stable flight of the FWMAV, a barrier Lyapunov function is used to make the flight states constrained in predefined regions. Based on the Lyapunov stability theory, the stability of the system is analyzed, and finally, the feasibility of RL in the control of a FWMAV is verified through simulation.

The proposed RL control scheme works well in ensuring the trajectory tracking of the FWMAV in the presence of output constraint and system uncertainty.

A novel RL algorithm based on actor–critic framework is applied to the control of a FWMAV with system uncertainty. For the stable and safe flight of the FWMAV, the output constraint problem is considered and solved by barrier Lyapunov function-based control.

After some critical notes on the long‐term regulation, requisite structure and requisite constitution as discussed by D. Sahal (Kybernetes 7, No. 1, 19–24, 1978), it is pointed out that W. Ross Ashby's Law of Requisite Variety implies a Principle of Variable Structure. Hereafter, a mathematical theory of amplifying regulation is given, and a new Law of Requisite Hierarchy is formulated. It is suggested to be fundamental in the theory of social organization.

This paper aims to propose cooperative control strategies for dual-arm robots in different human–robot collaborative tasks in assembly processes. The authors set three different regions where robot performs different collaborative ways: “teleoperate” region, “co-carry” region and “assembly” region. Human holds the “master” arm of dual-arm robot to operate the other “follower” arm by our proposed controller in “teleoperation” region. Limited by the human arm length, “follower” arm is teleoperated by human to carry the distant object. In the “co-carry” region, “master” arm and “follower” arm cooperatively carry the object to the region close to the human. In “assembly” region, “follower” arm is used for fixing the object and “master” arm coupled with human is used for assembly.

A human moving target estimated method is proposed for decreasing efforts for human to move “master” arm, radial basis functions neural networks are used to compensate for uncertainties in dynamics of both arms. Force feedback is designed in “master” arm controller for human to perceive the movement of “follower” arm. Experimental results on Baxter robot platform show the effectiveness of this proposed method.

Experimental results on Baxter robot platform show the effectiveness of our proposed methods. Different human-robot collaborative tasks in assembly processes are performed successfully under our cooperative control strategies for dual-arm robots.

In this paper, cooperative control strategies for dual-arm robots have been proposed in different human–robot collaborative tasks in assembly processes. Three different regions where robot performs different collaborative ways are set: “teleoperation” region, “co-carry” region and “assembly” region.

The purpose of this paper is to introduce an artificial bee colony-based Kalman filter algorithm along with an extended objective function to ensure the optimality of the estimator of the quadrotor in the presence of unknown measurement noise statistics.

Six degree-of-freedom mathematical model of the quadrotor is derived. Position controller for the quadrotor is designed. Kalman filter-based estimation algorithm is implemented in the sensor feedback loop. Artificial bee colony-based hybrid algorithm is used as an optimization method to handle the unknown noise statistics. Existing objective function is extended with a penalty term. Mathematical proof of the extended objective function is derived. Results of the proposed algorithm is compared with de facto genetic algorithm-based Kalman filter.

Artificial bee colony algorithm-based Kalman filter and extended objective function duo are able to optimize the measurement noise covariance matrix with an absolute error as low as 0.001 [m²]. Proposed method and function is capable of reducing the noise from 2 to 0.09 [m] for x-axis, 3.4 to 0.14 [m] for y-axis and 3.7 to 0.2 [m] for z-axis, respectively.

The motivation behind this paper is to bring a novel optimization-based solution for the estimation problem of the quadrotor when the measurement noise statistics are unknown along with an extended objective function to prevent the infeasible solutions with mathematical convergence analysis.

Imagining a new business model is a creative process that requires entrepreneurs to define how a firm can create and capture value with a new activity. The literature emphasises various tools and approaches for prototyping business models. The purpose of this paper is to investigate the suitability of story-making as a means of designing new business models and to shed light on its potential for stimulating creative entrepreneurial thinking.

This paper tests the use of story-making for business modelling in a real-life case to show its usefulness and shed light on its potential for stimulating creative entrepreneurial thinking.

The authors argue that story-making should be recognised as an approach to business modelling that can foster creativity and empathy. Building on insights from design thinking literature, the paper shows that planning for a long exploratory phase is necessary to allow system thinking. It also shows that anchors can act as intermediary stopping rule and help manage complexity.

The paper introduces an original method for crafting business models during early stages of the innovation process and argues that this method could also be used to design business processes, especially when they are not already formalised.