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Article

Esfandiar Maasoumi and Tong Xu

The purpose of this paper is to combine multidimensional welfare analysis and entropy metrics to derive not only the best relative weights but also substitution degree…

Abstract

Purpose

The purpose of this paper is to combine multidimensional welfare analysis and entropy metrics to derive not only the best relative weights but also substitution degree among different attributes to construct multidimensional indices of well-being with Chinese Household Income Project Survey 2002 data.

Design/methodology/approach

The authors follow Maasoumi’s two-step measures of multivariate inequality to calculate the inequality for three social groups in China, urban residents, migrants, and rural residents. The two-step approach provides an aggregation formula which is numerically identified in this paper based on a metric entropy distance measure between the distribution of the aggregate well-being functions, on the one hand, and the distribution of the self-reported “happiness” indicator. The authors compare the differences in relative weights and substitution degree for the three groups, and link them to some institutional factors.

Findings

The authors find that incorporating substitution among attributes, and taking into consideration group heterogeneity are very important in multidimensional analysis of well-being.

Originality/value

The two-step approach provides an aggregation formula which is numerically identified in this paper based on a metric entropy distance measure between the distribution of the aggregate well-being functions, on the one hand, and the distribution of the self-reported “happiness” indicator.

Details

Journal of Economic Studies, vol. 42 no. 1
Type: Research Article
ISSN: 0144-3585

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Book part

Esfandiar Maasoumi, Melinda Pitts and Ke Wu

We examine the cardinal gap between wage distributions of the incumbents and newly hired workers based on entropic distances which are well-defined welfare theoretic…

Abstract

We examine the cardinal gap between wage distributions of the incumbents and newly hired workers based on entropic distances which are well-defined welfare theoretic measures. Decomposition of several effects is achieved by identifying several counterfactual distributions of different groups. These go beyond the usual Oaxaca–Blinder decompositions at the (linear) conditional means. Much like quantiles, these entropic distances are well-defined inferential objects and functions whose statistical properties have recently been developed. Going beyond these strong rankings and distances, we consider weak uniform ranking of these wage outcomes based on statistical tests for stochastic dominance. The empirical analysis is focused on employees with at least 35 hours of work in the 1996–2012 monthly Current Population Survey (CPS). Among others, we find incumbent workers enjoy a better distribution of wages, but the attribution of the gap to wage inequality and human capital characteristics varies between quantiles. For instance, highly paid new workers are mainly due to human capital components, and in some years, even better wage structure.

Details

Essays in Honor of Peter C. B. Phillips
Type: Book
ISBN: 978-1-78441-183-1

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Article

J.A. Pardo and M.L. Vicente

Consideration is given to the problem of optimally choosing of a fixed number of experiments in sequential form from a class of available experiments. The applications of…

Abstract

Consideration is given to the problem of optimally choosing of a fixed number of experiments in sequential form from a class of available experiments. The applications of ø entropy measure in the sequential design of experiments is studied by defining ø terminal entropy. Finally, the process is established when a sufficient experiment exists. An illustrative example, which demonstrates the usefulness of the results obtained, is included.

Details

Kybernetes, vol. 23 no. 5
Type: Research Article
ISSN: 0368-492X

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Article

L. Pardo, D. Morales and I.J. Taneja

Fisher’s amount of information is the most parametric measure in the literature of statistics. However, not for every family of probability density functions do the…

Abstract

Fisher’s amount of information is the most parametric measure in the literature of statistics. However, not for every family of probability density functions do the well‐known regularity assumptions hold. To avoid this problem, several parametric measures have been proposed on the basis of divergence measures. In this work, parametric measures of information are obtained on the basis of the generalized Jensen difference divergence measures. When the regularity assumptions hold, their relations with Fisher’s amount of information are also studied.

Details

Kybernetes, vol. 24 no. 2
Type: Research Article
ISSN: 0368-492X

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Article

M.L. Menéndez, L. Pardo, D. Morales and M. Salicrú

Presents (h, ø)‐entropies as a generalization of ø‐entropies. Studies some applications of this function in Bayesian inference, especially in the comparison of…

Abstract

Presents (h, ø)‐entropies as a generalization of ø‐entropies. Studies some applications of this function in Bayesian inference, especially in the comparison of experiments. Also studies the relationship of the (h,ø)‐entropy criterion to the classical approaches of Blackwell (1951) and Lehmann (1959).

Details

Kybernetes, vol. 25 no. 2
Type: Research Article
ISSN: 0368-492X

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Article

Lutz Bellmann and Olaf Hübler

It is analyzed whether working from home improves or impairs the job satisfaction and the work–life balance and under which conditions.

Abstract

Purpose

It is analyzed whether working from home improves or impairs the job satisfaction and the work–life balance and under which conditions.

Design/methodology/approach

Blocks of influences on job satisfaction and work–life balance – personal traits, job characteristics, skills and employment properties – are estimated separately and in combination. To select the variables, the least angle regression is applied. The entropy balancing approach is used to determine causal effects. The study investigates whether imbalances are determined by private or job influences, whether firm-specific regulations and the selected control group affect the results and whether it only takes place during leisure time.

Findings

No clear effects of remote work on job satisfaction are revealed, but the impact on work–life balance is generally negative. If the imbalance is conditioned by private interests, this is not corroborated in contrast to job conditioned features. Employees working from home are happier than those who want to work at home, job satisfaction is higher and work–life balance is not worse under a strict contractual agreement than under a nonbinding commitment.

Originality/value

A wide range of personality traits, skills, employment properties and job characteristics are incorporated as determinants. The problem of causality is investigated. It is analyzed whether the use of alternative control and treatment groups leads to different results. The empirical investigation is based on new German data with three waves.

Details

International Journal of Manpower, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-7720

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Article

Mehmet Caner Akay and Hakan Temeltaş

Heterogeneous teams consisting of unmanned ground vehicles and unmanned aerial vehicles are being used for different types of missions such as surveillance, tracking and…

Abstract

Purpose

Heterogeneous teams consisting of unmanned ground vehicles and unmanned aerial vehicles are being used for different types of missions such as surveillance, tracking and exploration. Exploration missions with heterogeneous robot teams (HeRTs) should acquire a common map for understanding the surroundings better. The purpose of this paper is to provide a unique approach with cooperative use of agents that provides a well-detailed observation over the environment where challenging details and complex structures are involved. Also, this method is suitable for real-time applications and autonomous path planning for exploration.

Design/methodology/approach

Lidar odometry and mapping and various similarity metrics such as Shannon entropy, Kullback–Leibler divergence, Jeffrey divergence, K divergence, Topsoe divergence, Jensen–Shannon divergence and Jensen divergence are used to construct a common height map of the environment. Furthermore, the authors presented the layering method that provides more accuracy and a better understanding of the common map.

Findings

In summary, with the experiments, the authors observed features located beneath the trees or the roofed top areas and above them without any need for global positioning system signal. Additionally, a more effective common map that enables planning trajectories for both vehicles is obtained with the determined similarity metric and the layering method.

Originality/value

In this study, the authors present a unique solution that implements various entropy-based similarity metrics with the aim of constructing common maps of the environment with HeRTs. To create common maps, Shannon entropy–based similarity metrics can be used, as it is the only one that holds the chain rule of conditional probability precisely. Seven distinct similarity metrics are compared, and the most effective one is chosen for getting a more comprehensive and valid common map. Moreover, different from all the studies in literature, the layering method is used to compute the similarities of each local map obtained by a HeRT. This method also provides the accuracy of the merged common map, as robots’ sight of view prevents the same observations of the environment in features such as a roofed area or trees. This novel approach can also be used in global positioning system-denied and closed environments. The results are verified with experiments.

Details

Industrial Robot: the international journal of robotics research and application, vol. 47 no. 6
Type: Research Article
ISSN: 0143-991X

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Article

Bhumeshwar Patle, Shyh-Leh Chen, Brijesh Patel, Sunil Kumar Kashyap and Sudarshan Sanap

With the increasing demand for surveillance and smart transportation, drone technology has become the center of attraction for robotics researchers. This study aims to…

Abstract

Purpose

With the increasing demand for surveillance and smart transportation, drone technology has become the center of attraction for robotics researchers. This study aims to introduce a new path planning approach to drone navigation based on topology in an uncertain environment. The main objective of this study is to use the Ricci flow evolution equation of metric and curvature tensor over angular Riemannian metric, and manifold for achieving navigational goals such as path length optimization at the minimum required time, collision-free obstacle avoidance in static and dynamic environments and reaching to the static and dynamic goals. The proposed navigational controller performs linearly and nonlinearly both with reduced error-based objective function by Riemannian metric and scalar curvature, respectively.

Design/methodology/approach

Topology and manifolds application-based methodology establishes the resultant drone. The trajectory planning and its optimization are controlled by the system of evolution equation over Ricci flow entropy. The navigation follows the Riemannian metric-based optimal path with an angular trajectory in the range from 0° to 360°. The obstacle avoidance in static and dynamic environments is controlled by the metric tensor and curvature tensor, respectively. The in-house drone is developed and coded using C++. For comparison of the real-time results and simulation results in static and dynamic environments, the simulation study has been conducted using MATLAB software. The proposed controller follows the topological programming constituted with manifold-based objective function and Riemannian metric, and scalar curvature-based constraints for linear and nonlinear navigation, respectively.

Findings

This proposed study demonstrates the possibility to develop the new topology-based efficient path planning approach for navigation of drone and provides a unique way to develop an innovative system having characteristics of static and dynamic obstacle avoidance and moving goal chasing in an uncertain environment. From the results obtained in the simulation and real-time environments, satisfactory agreements have been seen in terms of navigational parameters with the minimum error that justifies the significant working of the proposed controller. Additionally, the comparison of the proposed navigational controller with the other artificial intelligent controllers reveals performance improvement.

Originality/value

In this study, a new topological controller has been proposed for drone navigation. The topological drone navigation comprises the effective speed control and collision-free decisions corresponding to the Ricci flow equation and Ricci curvature over the Riemannian metric, respectively.

Details

Industrial Robot: the international journal of robotics research and application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-991X

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Article

AUREL AVRAMESCU

Aiming to provide a common theoretical foundation for all known biblio‐metric laws, the author starts from a systemic view of the information transfer process and…

Abstract

Aiming to provide a common theoretical foundation for all known biblio‐metric laws, the author starts from a systemic view of the information transfer process and assimilates it with a physical diffusion process, in particular the conduction of heat in solids. Previous literature induces in the properly ranked space of new authors an interest potential (temperature) confirmed by exchange of reference‐citation pairs, and driving a controlled information flow. The model gives its distribution for given initial and borderline conditions, allowing at the same time the establishment of new definitions for informational energy and entropy, which are coherent with the corresponding physical ones. The theory shows that impulsory energy supply is bound to negative entropy inflow which brakes the normal entropy ‘production’ in the ‘dissipative’ structures of the considered system. In this way the introduction of information into concrete thermodynamic systems analysis can hopefully be expected.

Details

Journal of Documentation, vol. 36 no. 4
Type: Research Article
ISSN: 0022-0418

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Book part

Amos Golan and Robin L. Lumsdaine

Although in principle prior information can significantly improve inference, incorporating incorrect prior information will bias the estimates of any inferential analysis…

Abstract

Although in principle prior information can significantly improve inference, incorporating incorrect prior information will bias the estimates of any inferential analysis. This fact deters many scientists from incorporating prior information into their inferential analyses. In the natural sciences, where experiments are more regularly conducted, and can be combined with other relevant information, prior information is often used in inferential analysis, despite it being sometimes nontrivial to specify what that information is and how to quantify that information. In the social sciences, however, prior information is often hard to come by and very hard to justify or validate. We review a number of ways to construct such information. This information emerges naturally, either from fundamental properties and characteristics of the systems studied or from logical reasoning about the problems being analyzed. Borrowing from concepts and philosophical reasoning used in the natural sciences, and within an info-metrics framework, we discuss three different, yet complimentary, approaches for constructing prior information, with an application to the social sciences.

Details

Essays in Honor of Aman Ullah
Type: Book
ISBN: 978-1-78560-786-8

Keywords

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