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Presents over sixty abstracts summarising the 1999 Employment Research Unit annual conference held at the University of Cardiff. Explores the multiple impacts of globalization on work and employment in contemporary organizations. Covers the human resource management implications of organizational responses to globalization. Examines the theoretical, methodological, empirical and comparative issues pertaining to competitiveness and the management of human resources, the impact of organisational strategies and international production on the workplace, the organization of labour markets, human resource development, cultural change in organisations, trade union responses, and trans‐national corporations. Cites many case studies showing how globalization has brought a lot of opportunities together with much change both to the employee and the employer. Considers the threats to existing cultures, structures and systems.

This chapter examines herd behavior across national borders. A dynamic latent factor model with Gibbs sampling is used to decompose the national herd behavior into the world, regional, and country-specific components. Testing the daily data from 2000 through 2014 for 47 countries, we find that the impact of world factor on national herd behavior is short-lived. This study indicates that world and regional factors play a significant role in explaining the variations of national herd behavior, constituting 33% of the herding variability. The significance of world and regional components is likely to produce a biased herding estimator.

Government policy can alleviate inequities in living standards. Disabled people often qualify for government assistance which is one way that their living standard can improve, although arbitrary systems for distributing assistance are not likely to serve equity objectives. The purpose of this paper is to indicate the key variables to which government should direct attention, in order to alleviate both horizontal and vertical inequity in grants to disabled people.

There is no literature, either theoretical or empirical, that specifically addresses this problem. This paper invokes important economic concepts associated with the nineteenth century English philosopher/economist, John Stuart Mill, as well as the 1998 Nobel Laureate in Economics, Amartya Sen. Mill's general conception of how government should behave in treating citizens was elaborated subsequently in the public finance literature on principles of taxation. These notions are about “the equal treatment of equals” and “the unequal treatment of unequals”. Sen's recent discussion of the “conversion handicap” from his general framework of capabilities is highly relevant to the question addressed here.

These concepts, applied with some analytical tools of algebra and geometry, show that Mill's principles can combine with Sen's into a relevant conceptual framework. The central principles and concepts for policy formation on the standard of living for disabled people are not random; they can be specified with clarity.

This paper contributes the relevant conceptual “yardsticks” by which policy for distributing assistance to disabled people can be evaluated. Steps, towards devising better approaches to the distribution of assistance to disabled people can now be taken.

A chaotic system is a nonlinear deterministic system that displays complex, noisy‐like and unpredictable behavior. The interest in chaotic systems lies mostly upon their complex, unpredictable behavior, and extreme sensitivity to initial conditions as well as parameter variations. Based on wavelet neural network's (WNN) online approximation ability, the purpose of this paper is to propose an adaptive Gaussian wavelet neural control (AGWNC) system to control a chaotic system.

The proposed AGWNC system is composed of a wavelet neural controller and a compensation tangent controller. The wavelet neural controller utilizes a Gaussian WNN to mimic an ideal controller, and the compensation tangent controller is designed to compensate the approximation error between the ideal and the wavelet neural controllers. The controller parameters of the proposed AGWNC can online tune in the Lyapunov sense, thus the uniformly ultimately bounded stability of closed‐loop system can be guaranteed.

The proposed AGWNC system is applied to a chaotic system. Simulation results are used to demonstrate the effectiveness and performance of the proposed AGWNC scheme. Simulation results show that not only the favorable control performance can be achieved but also the control efforts without any chattering phenomena. Moreover, all controller parameters can be online tuning by the derived adaptive laws based on the Lyapunov function.

The proposed AGWNC approach is interesting for the design of an intelligent control scheme. The main contributions of this paper are: the overall closed‐loop control system is globally stable in uniform ultimate boundedness; the tracking error can be asymptotically attenuated to a desired small level around zero by appropriate chosen parameters and learning rates; and the AGWNC system can achieve favorable tracking performance.

The concept of organizational identity became a subject of interest within the academic milieu in the mid‐1980s. In this paper, we propose the construct of legacy identities, those persistent identities that, first, endure over time at different levels of expression and, second, are comprised of resilient ideals from the past that represent the perceived persistent character of what the organization used to be. This construct is derived from a case study that portrays the radical transformation of a former state‐owned Brazilian company that became a subsidiary of a North American firm and survived the crisis that originated from its parent company’s debacle. Building on data from the case study, we develop a framework that shows the salience of different identities through time in the company and seek to explain the dynamics underlying these changes.

The purpose of this paper is to propose a new hybrid algorithm, named improved plant growth simulation algorithm and particle swarm optimization hybrid algorithm (PGSA–PSO hybrid algorithm), for solving structural optimization problems.

To further enhance the optimization efficiency and precision of this algorithm, the optimization solution process of PGSA–PSO comprises two steps. First, an excellent initial growth point is selected by PSO. Then, the global optimal solution can be obtained quickly by PGSA and its improved strategy called growth space adjustment strategy. A typical mathematical example is provided to verify the capacity of the new hybrid algorithm to effectively improve the global search capability and search efficiency of PGSA. Moreover, PGSA–PSO is applied to the optimization design of a suspended dome structure.

Through typical mathematical example, the improved strategy can improve the optimization efficiency of PGSA considerably, and an initial growth point that falls near the global optimal solution can be obtained. Through the optimization of the pre-stress of a suspended dome structure, compared with other methods, the hybrid algorithm is effective and feasible in structural optimization.

Through the examples of suspended dome structure, it shows that the optimization efficiency and precision of PGSA–PSO are better than those of other algorithms and methods. PGSA–PSO is effective and feasible in structural optimization problems such as pre-stress optimization, size optimization, shape optimization and even topology optimization.