The author presents new estimates of the probability weighting functions found in rank-dependent theories of choice under risk. These estimates are unusual in two senses. First…
Abstract
The author presents new estimates of the probability weighting functions found in rank-dependent theories of choice under risk. These estimates are unusual in two senses. First, they are free of functional form assumptions about both utility and weighting functions, and they are entirely based on binary discrete choices and not on matching or valuation tasks, though they depend on assumptions concerning the nature of probabilistic choice under risk. Second, estimated weighting functions contradict widely held priors of an inverse-s shape with fixed point well in the interior of the (0,1) interval: Instead the author usually finds populations dominated by “optimists” who uniformly overweight best outcomes in risky options. The choice pairs used here mostly do not provoke similarity-based simplifications. In a third experiment, the author shows that the presence of choice pairs that provoke similarity-based computational shortcuts does indeed flatten estimated probability weighting functions.
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Martin Götz and Ernest H. O’Boyle
The overall goal of science is to build a valid and reliable body of knowledge about the functioning of the world and how applying that knowledge can change it. As personnel and…
Abstract
The overall goal of science is to build a valid and reliable body of knowledge about the functioning of the world and how applying that knowledge can change it. As personnel and human resources management researchers, we aim to contribute to the respective bodies of knowledge to provide both employers and employees with a workable foundation to help with those problems they are confronted with. However, what research on research has consistently demonstrated is that the scientific endeavor possesses existential issues including a substantial lack of (a) solid theory, (b) replicability, (c) reproducibility, (d) proper and generalizable samples, (e) sufficient quality control (i.e., peer review), (f) robust and trustworthy statistical results, (g) availability of research, and (h) sufficient practical implications. In this chapter, we first sing a song of sorrow regarding the current state of the social sciences in general and personnel and human resources management specifically. Then, we investigate potential grievances that might have led to it (i.e., questionable research practices, misplaced incentives), only to end with a verse of hope by outlining an avenue for betterment (i.e., open science and policy changes at multiple levels).
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Erel Avineri and Eran Ben-Elia
This chapter explores Prospect Theory — a descriptive model of modelling individual choice making under risk and uncertainty, and its applications to a range of travel behaviour…
Abstract
Purpose
This chapter explores Prospect Theory — a descriptive model of modelling individual choice making under risk and uncertainty, and its applications to a range of travel behaviour contexts.
Theory
The chapter provides background on Prospect Theory, its basic assumptions and formulations, and summarises some of its theoretical developments, applications and evidence in the field of transport research.
Findings
A body of empirical evidence has accumulated showing that the principle of maximisation of expected utility provides limited explanation of travel choices under risk and uncertainty. Prospect Theory can be seen as an alternative and promising framework for travel choice modelling (although not without theoretical and practical controversy). These findings are supported by empirical observations reported in the literature reviewed in this chapter.
Originality and value
The chapter provides a detailed account of the design and results of accumulated research in travel behaviour research that is based on Prospect Theory’s observations, insights and formulations. The potential of Prospect Theory for particular decision-making in travel behaviour research is articulated, main findings are presented and discussed, and limitations are identified, leading to further research needs.
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Daifeng Zhang, Haibin Duan and Yijun Yang
The purpose of this paper is to propose a control approach for small unmanned helicopters, and a novel swarm intelligence algorithm is used to optimize the parameters of the…
Abstract
Purpose
The purpose of this paper is to propose a control approach for small unmanned helicopters, and a novel swarm intelligence algorithm is used to optimize the parameters of the proposed controller.
Design/methodology/approach
Small unmanned helicopters have many advantages over other unmanned aerial vehicles. However, the manual operation process is difficult because the model is always instable and coupling. In this paper, a novel optimized active disturbance rejection control (ADRC) approach is presented for small unmanned helicopters. First, a linear attitude model is built in hovering condition according to small perturbation linearization. To realize decoupling, this model is divided into two parts, and each part is equipped with an ADRC controller. Finally, a novel Levy flight-based pigeon-inspired optimization (LFPIO) algorithm is developed to find the optimal ADRC parameters and enhance the performance of controller.
Findings
This paper applies ADRC method to the attitude control of small unmanned helicopters so that it can be implemented in practical flight under complex environments. Besides, a novel LFPIO algorithm is proposed to optimize the parameters of ADRC and is proved to be more efficient than other homogenous methods.
Research limitations/implications
The model of proposed controller is built in the hovering action, whereas it cannot be used in other flight modes.
Practical implications
The optimized ADRC method can be implemented in actual flight, and the proposed LFPIO algorithm can be developed in other practical optimization problems.
Originality/value
ADRC method can enhance the response and robustness of unmanned helicopters which make it valuable in actual environments. The proposed LFPIO algorithm is proved to be an effective swarm intelligence optimizer, and it is convenient and valuable to apply it in other optimized systems.
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Abstract
Purpose
To design effective and practical controllers that use the adaptive fuzzy approaches and are applicable to helicopters.
Design/methodology/approach
Based on Takagi‐Sugeno fuzzy systems, a new direct adaptive fuzzy control scheme is developed for a class of nonlinear multiple‐input‐multiple‐output systems. A simple observer is designed to generate an error signal for the adaptive law. The system states of the system are not required to be available for measurement.
Findings
The overall adaptive scheme guarantees all the signals involved being uniformly bounded in the Lyapunov sense.
Research limitations/implications
The implementation of this research work needs further investigation.
Practical implications
The simplicity of the design algorithm facilitates the application of the design to helicopters by the use of Matlab.
Originality/value
Experimental results of a two degree of freedom helicopter are presented to confirm the usefulness of the proposed new control scheme.
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Hoang Tien Nguyen, Doan Minh Duc Le, Thien Thong Minh Ho and Phuong Mai Nguyen
This study aims to point out the importance and the relevance of sustainability issues and the need for their enhancement in the contemporary model of corporate social…
Abstract
Purpose
This study aims to point out the importance and the relevance of sustainability issues and the need for their enhancement in the contemporary model of corporate social responsibility (CSR) as the top priority for business entities. Furthermore, it also highlights ways to enhance sustainability in the contemporary CSR model in the fast fashion industry of developing countries.
Design/methodology/approach
Literature review has been extensively done through available databases, including ProQuest and ScienceDirect.
Findings
This study delivers a full insight into the current state of research on the CSR model and sustainability in developing countries. The prevalent corporate environmental sustainability practices of global apparel brands are identified to propose ways to enhance sustainability in the contemporary CSR model.
Research limitations/implications
The growth of fast fashion industry brings the risks of unsustainability to developing countries. Thus, it is a must for the garment and textile companies to enhance a sustainable CSR model through promoting sustainable leadership and integrating corporate culture.
Originality/value
To the best of author’s knowledge, this study is the first to emphasise the role of sustainable leadership in promoting a sustainable CSR model in the fast fashion industry of developing countries.
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Anna Marie Johnson, Claudene Sproles, Robert Detmering and Jessica English
The purpose of this paper is to provide a selected bibliography of recent resources on library instruction and information literacy.
Abstract
Purpose
The purpose of this paper is to provide a selected bibliography of recent resources on library instruction and information literacy.
Design/methodology/approach
The paper introduces and annotates periodical articles, monographs, and audiovisual material examining library instruction and information literacy.
Findings
Information is provided about each source, and the paper discusses the characteristics of current scholarship, and describes sources that contain unique scholarly contributions and quality reproductions.
Originality/value
The information may be used by librarians and interested parties as a quick reference to literature on library instruction and information literacy.
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Slim Frikha, Mohamed Djemel and Nabil Derbel
The purpose of this paper is to present an adaptive neuro‐sliding mode control scheme for uncertain nonlinear systems with Lyapunov approach.
Abstract
Purpose
The purpose of this paper is to present an adaptive neuro‐sliding mode control scheme for uncertain nonlinear systems with Lyapunov approach.
Design/methodology/approach
The paper focuses on neural network (NN) adaptive control for nonlinear systems in the presence of parametric uncertainties. The plant model structure is represented by a NNs system. The essential idea of the online parametric estimation of the plant model is based on a comparison of the measured state with the estimated one. The proposed adaptive neural controller takes advantages of both the sliding mode control and proportional integral (PI) control. The chattering phenomenon is attenuated and robust performances are ensured. Based on Lyapunov stability theorem, the proposed adaptive neural control system can guarantee the stability of the whole closed‐loop system and obtain good‐tracking performances. Adaptive laws are proposed to adjust the free parameters of the neural models.
Findings
Simulation results show that the adaptive neuro‐sliding mode control approach works satisfactorily for nonlinear systems in the presence of parametric uncertainties.
Originality/value
The proposed adaptive neuro‐sliding mode control approach is a mixture of classical neural controller with a supervisory controller. The PI controller is used to attenuate the chattering phenomena. Based on the Lyapunov stability theorem, it is rigorously proved that the stability of the whole closed‐loop system is ensured and the tracking performance is achieved.