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In this chapter, we reflect on cognitive aids and their role in strategy work. Strategy research and practice abound with frameworks, models, tools, and processes meant to describe and guide the strategy work of managers. These are all examples of cognitive aids. These aids guide and support managerial cognition, the way managers make sense of the world. What we collectively call the cognitive aids of strategy have a profound impact on the way managers learn about, conceptualize, share, and enact strategy work and strategies in their organizations. Despite the importance of their cognitive role, many cognitive aids in strategy are presented without reference to the underlying cognitive theory that explains why and how the aid might be useful. Tools are presented as useful for management thinking, but without any substantive reflection or exploration of the cognitive reasons. In this chapter, we provide a definition of cognitive aids in strategy and begin exploring the landscape of cognitive theories that can explain why something might be a cognitive aid. We then briefly outline the contributions to the edited volume “Cognitive Aids in Strategy,” and end with an invitation to expand your exploration beyond.

Improving a startup’s ability to obtain funding is critical to the survival of the organization. Although existing studies have observed various biases in investment decisions, few have studied the neural mechanisms behind such behavioral observations. We propose to apply cutting-edge neuroscientific techniques to uncover the neural processes engaged during pitches by entrepreneurs to investors and to use this new knowledge to identify strategy artifacts promoting pitch success. We hypothesize that pitches are dynamically shaped by covert cognitive, emotional, and social processes, which are in turn influenced by tactical approach (story-telling vs dry facts), physical context (online vs in-person), and demographics (gender, ethnicity). The role of inter-brain synchrony (i.e., correlation of cortical activity between brains) – within the startup team or between the entrepreneurs and investors – in pitch outcomes remains unknown. By uncovering the covert processes that mediate pitch outcomes, we provide an evidence-based, scientific approach to improving pitch success.

The purpose of this study is to propose a new mathematical model that integrates strategic decision-making with tactical-operational decision-making in order to optimize production and scheduling decisions.

This study presents a multi-objective optimization framework to make production planning, scheduling and maintenance decisions. An epsilon-constraint method is used to solve small instances of the model, while new hybrid optimization algorithms, including multi-objective particle swarm optimization (MOPSO), non-dominated sorting genetic algorithm, multi-objective harmony search and improved multi-objective harmony search (IMOHS) are developed to address the high complexity of large-scale problems.

The computational results demonstrate that the metaheuristic algorithms are effective in obtaining economic solutions within a reasonable computational time. In particular, the results show that the IMOHS algorithm is able to provide optimal Pareto solutions for the proposed model compared to the other three algorithms.

This study presents a new mathematical model that simultaneously determines green production planning and scheduling decisions by minimizing the sum of the total cost, makespan, lateness and energy consumption criteria. Integrating production and scheduling of a shop floor is critical for achieving optimal operational performance in production planning. To the best of the authors' knowledge, the integration of production planning and maintenance has not been adequately addressed.

The purpose of this paper is to obtain values that stabilize the lateral and longitudinal flight of the quadrotor for which the morphing amount and the best Proportional-Integral-Derivative (PID) coefficients are determined by using the simultaneous perturbation stochastic approximation (SPSA) optimization algorithm.

Quadrotor consists of body and arms; there are propellers at the ends of the arms to take off and rotors that rotate them. By reducing the angle between mechanism 1 and the rotors with the horizontal plane, the angle between mechanism 2 and the arms, the rotors rise and different configurations are obtained. Conventional multi-rotor aircraft has a fixed fuselage and does not need a tail rotor to change course as helicopters do. The translational and rotational movements are provided by the rotation of the rotors of the aircraft at different speeds by creating moments about the geometric center in 6-degree-of-freedom (DOF) space. These commands sent from the ground are provided by the flight control board in the aircraft. The longitudinal and lateral flight stability and properties of different configurations evaluated by dynamic analysis and simulations in 6 DOF spaces are investigated. An algorithm and PID controller are being developed using SPSA to achieve in-flight position and attitude control of an active deformable aircraft. The results are compared with the results of the literature review and the results of the previous article.

With SPSA, the best PID coefficients were obtained in case of morphing.

The effects of quadrotor arm height and hub angle changes affect flight stability. With the SPSA optimization method presented in this study, the attitude is quickly stabilized.

With the optimization method, the most suitable PID coefficients and angle values for the lateral and longitudinal flight stability of the quadrotor are obtained.

The transition rate and PID coefficients are determined by using the optimization method, which is advantageous in terms of cost and practicality.

With the proposed method, the aircraft can change shape to adapt to different environments, and the parameters required for more stable flight for each situation will be calculated, and this will be obtained more quickly and safely with the SPSA optimization method.

It is widely evident that trust and commitment are important pillars for strengthening the relationship between financial service firms and their customers. However, it has not been explored how the service quality, perceived cost and role of agents are important for financial service firms. To overcome this gap, this study aims to investigate the role of service quality, perceived cost and the role of agents as the commitment–trust factors in the financial insurance service (Takaful) in Malaysia, enhancing customer satisfaction.

The study follows a quantitative design in which primary data was collected using a survey instrument. The measurement instrument was adapted from the previous research, and data were collected from 264 customers of the Takaful financial service organizations in Malaysia. The data were analyzed using variance-based structural equational modeling in Smart-PLS software.

This research has revealed several useful insights that demonstrate a significant impact on service quality, perceived cost and the agents’ role in forging close relationships with their customers. Corporate image has a moderating role in relationships and has significantly impacted takaful insurance companies. The results imply that regardless of the corporate image of the financial service organizations, customers are concerned about the prices and the quality of the agents’ services.

In this study, only the predictors such as service quality, perceived costs and agents’ roles as trust–commitment factors were examined to determine customer satisfaction. Other investigations are highly recommended, such as value co-creation in takaful, takaful customer experience and takaful trust. This study offers insights to takaful insurance companies on how to keep up a positive corporate image, which will boost their trust–commitment factors and ultimately increase customer satisfaction.

By presenting commitment–trust factors and company image in an identifiable framework, the current study has expanded the discussion on takaful financial insurance services. The methodology is developed and rigorously tested to gauge customer satisfaction in takaful financial service organizations’ context.

The purpose of this paper is to optimize the simultaneous flight performance of a hexarotor unmanned aerial vehicle (UAV) by using simultaneous perturbation stochastic approximation (i.e. SPSA), deep neural network and proportional integral derivative (i.e. PID) according to varying arm length (i.e. morphing).

In this paper, proper PID gain coefficients and morphing ratio were obtained using the stochastic optimization method, also known as SPSA to maximize flight efficiency. Because it is difficult to establish an analytical connection between the morphing ratio and hexarotor moments of inertia, the deep neural network was used to obtain the moments of inertia according to the morphing ratio. By using SPSA and deep neural network, the best performance indexes were obtained and both longitudinal and lateral flight simulations were performed with the obtained data.

With SPSA, the best PID coefficients and morphing ratio are obtained for both longitudinal and lateral flight. Because the hexarotor solid body model changes according to the morphing ratio, the moment of inertia values used in the simulations also change. According to the morphing ratio, the moment of inertia values was obtained with the deep neural network over a created data set.

It takes a long time to obtain the morphing ratio suitable for the hexarotor model and the PID gain coefficients suitable for this morphing ratio. However, this situation can be overcome with the proposed SPSA. In addition, it takes a long time to obtain the appropriate moments of inertia according to the morphing ratio. However, in this case, it was overcome using the deep neural network.

Determining the morphing ratio and PID gain coefficients using the optimization method, as well as determining the moments of inertia using the deep neural network, is very useful as it can increase the efficiency of hexarotor flight and flight efficiently with different arm lengths. With the proposed method, the hexarotor design performance criteria (i.e. rise time, settling time and overshoot) values were significantly improved compared to similar studies.

Determining the hexarotor flight parameters using SPSA and deep neural network provides advantages in terms of time, cost and applicability.

The hexarotor flight efficiency is improved with the proposed SPSA and deep neural network approaches. In addition, the desired flight parameters can be obtained more quickly and reliably with the proposed approaches. The design performance criteria were also improved, enabling the hexarotor UAV to follow the given trajectory in the best way and providing convenience for end users. SPSA was preferred because it converged faster than other methods. While other methods perform 2n operations per iteration, SPSA only performs two operations. To obtain the moment of inertia, many physical parameter values of the UAV are required in the existing methods. In the proposed method, by creating a date set, only arm length and moment of inertia were estimated without the need to obtain physical parameters with the deep neural network structure.

This paper aims to further develop stator permanent magnet (PM) type memory machines by providing generalized design guidelines for double-stator memory machines (DSMMs) with hybrid PMs. This paper discusses the design experience of DSMMs and presents a comparative study of radial magnetization (RM) and circumferential magnetization (CM) types.

It begins with an introduction to RM and CM operating principles and magnetization mechanisms. Then, a comparative study is conducted for one of the RM-DSMM rotor pole pairs, inner and outer stator clamping angles and low coercive force PMs thickness. Finally, the two machines’ finite element simulation performance is compared. The validity of the proposed machine structure is demonstrated.

In this paper, the double-stator structure is extended to parallel hybrid PM memory machines, and two novel DSMMs with RM and CM configurations are proposed. Two types of DSMMs have PMs and magnetizing windings on the inner stator and armature windings on the outer stator. The main difference between the two is the arrangement of PMs on the inner stator.

Conventional stator PM memory machines have geometrical space conflicts between the PM and armature windings. The proposed double-stator structure can alleviate these conflicts and increase the torque density accordingly. In addition, this paper contributes to comparing the arrangement of hybrid PMs for DSMMs.

In this paper, the brain potential changes caused by touching fabrics for handle evaluation were recorded by event related potential (ERP) method, compared with subjective evaluation scores and physical index of KES, explore the cognitive mechanism of the transformation of tactile sensation into neural impulses triggered by subtle mechanical stimuli such as material, texture, density and morphology in fabrics. By combining subjective evaluation of fabric tactile sensation, objective physical properties of fabrics and objective neurobiological signals, explore the neurophysiological mechanism of tactile cognition and the signal characteristics and time process of tactile information processing.

The ERP technology was first proposed by a British psychologist named Grey Walter. It is an imaging technique of noninvasive brain cognition, whose potential changes are related to the human physical and mental activities. ERP is different from electroencephalography (EEG) and evoked potentials (EP) on the fact that it cannot only record stimulated physical information which is transmitted to brain, but also response to the psychological activities which related to attention, identification, comparison, memory, judgment and cognition as well as to human’s neural physiological changes which are caused by cognitive process of the feeling by stimulation.

According to potential changes in the cerebral cortex evoked by touching four types of silk fabrics, human brain received the physical stimulation in the early stage (50 ms) of fabrics handle evaluation, and the P50 component amplitude showed negative correlation with fabric smoothness sensations. Around 200 ms after tactile stimulus onset, the amplitude of P200 component show positive correlation with the softness sensation of silk fabrics. The relationship between the amplitude of P300 and the sense of smoothness and softness need further evidence to proof.

In this paper, the brain potential changes caused by touching fabrics for handle evaluation were recorded by event related potential (ERP) method, compared with subjective evaluation scores and physical index of KES, the results shown that the maximum amplitude of P50 component evoked by fabric touching is related to the fabrics’ smoothness and roughness emotion, which means in the early stage processing of tactile sensation, the rougher fabrics could arouse more attention. In addition, the amplitude of P200 component shows positive correlation with the softness sensation of silk fabrics.

This study investigates the impact of three parameters such as: number of LED chips, pitch and LED power on the junction temperature of LEDs using a best heat sink configuration selected according to a lower temperature. This study provides valuable insights into how to design LED arrays with lower junction temperatures.

To determine the best configuration of a heat sink, a numerical study was conducted in Comsol Multiphysics on 10 different configurations. The configuration with the lowest junction temperature was selected for further analysis. The number of LED chips, pitch and LED power were then varied to determine the optimal configuration for this heat sink. A general equation for the average LED temperature as a function of these three factors was derived using Minitab software.

Among 10 configurations of the rectangular heat sink, we deduce that the best configuration corresponds to the first design having 1 mm of width, 0.5 mm of height and 45 mm of length. The average temperature for this design is 50.5 C. For the power of LED equal to 50 W–200 W, the average temperature of this LED drops when the number of LED chips reduces and the pitch size decreases. Indeed, the best array-LED corresponds to 64 LED chips and a pitch size of 0.5 mm. In addition, a generalization equation for average temperature is determined as a function of the number of LED chips, pitch and power of LED which are key factors for reducing the Junction temperature.

The study is original in its focus on three factors that have not been studied together in previous research. A numerical simulation method is used to investigate the impact of the three factors, which is more accurate and reliable than experimental methods. The study considers a wide range of values for the three factors, which allows for a more comprehensive understanding of their impact. It derives a general equation for the average temperature of the LED, which can be used to design LED arrays with desired junction temperatures.

This paper investigates gender disparity in investment decisions within the popular American TV show Shark Tank.

The research uses a comprehensive dataset of 925 pitches from 14 seasons and 316 episodes, covering August 2009 to May 2023.

Contrary to previous studies, the findings indicate that female entrepreneurs do n'ot face discrimination in terms of their pitching success rates, regardless of their industry affiliation. However, the authors did observe that female entrepreneurs tend to receive lower valuations, both self-assessed and in final deals. This suggests a self-imposed gender gap in venture capital and angel investing, likely stemming from lower entrepreneurial aspirations among women.

To tackle this issue, the authors propose promoting female venture capital by increasing the representation of female entrepreneurs and business angels on Shark Tank. Such role models can inspire aspiring women in these fields. Additionally, the authors believe that mixed-gender founder teams, comprising both men and women, can play a significant role in developing promising startups with viable business models.