Challenges for expatriate managers:an exploration of cross-cultural management, adjustment, and training issues faced by Anglo-American managers in Hong Kong

This field work study furthers understanding about expatriate management, in particular, the nature of cross-cultural management in Hong Kong involving Anglo-American expatriate and Chinese host national managers, the important features of adjustment for expatriates living and working there, and the type of training which will assist them to adjust and to work successfully in this Asian environment. Qualitative and quantitative data on each issue was gathered during in-depth interviews in Hong Kong, using structured interview schedules, with 39 expatriate and 31 host national managers drawn from a cross-section of functional areas and organizations. Despite the adoption of Western technology and the influence of Western business practices, micro-level management in Hong Kong retains a cultural specificity which is consistent with the norms and values of Chinese culture. There are differences in how expatriates and host nationals define their social roles, and Hong Kong's recent colonial history appears to influence cross-cultural interpersonal interactions. The inability of the spouse and/or family to adapt to Hong Kong is identified as a major reason for expatriate assignments to fail, though the causes have less to do with living away from family and friends, than with Hong Kong's highly urbanized environment and the heavy demands of work. Culture shock is not identified as a major problem, but in Hong Kong micro-level social factors require greater adjustment than macro-level societal factors. The adjustment of expatriate managers is facilitated by a strong orientation towards career development and hard work, possession of technical/professional expertise, and a willingness to engage in a process of continuous 'active learning' with respect to the host national society and culture. A four-part model of manager training suitable for Hong Kong is derived from the study data. It consists of a pre-departure briefing, post-arrival cross-cultural training, language training in basic Cantonese and in how to communicate more effectively in English with non-native speakers, and the assignment of a mentor to newly arrived expatriate managers.

Market quality changes in the London Stock Market

This paper examines the impact that the introduction of a closing call auction had on market quality at the London Stock Exchange. Using estimates from the partial adjustment with noise model of Amihud and Mendelson [Amihud, Y., Mendelson, H., 1987. Trading mechanisms and stock returns: An empirical investigation. Journal of Finance 42, 533–553] we show that opening and closing market quality improved for participating stocks. When we stratify our sample securities into five groups based on trading activity we find that the least active securities experience the greatest improvements to market quality. A control sample of stocks are not characterized by discernable changes to market quality.

Explaining volatility and serial correlation in opening and closing returns:a study of the FT-30 components

In this paper the performance of opening and closing returns, for the components of the FT-30 will be studied. It will be shown that for these stocks opening returns have higher volatility and a greater tendency towards negative serial correlation than closing returns. Unlike previous studies this contrasting performance cannot solely be attributed to differences in the trading mechanism across the trading day. All the stocks used in our sample trade thought the day using a uniform trading mechanism. In this paper, we suggest that it is differences in the speed that closing and opening returns adjust to new information that causes differences in return performance. By estimating the Amihud and Mendelson (1987) [Amihud, Yakov, & Mendelson, Haim (1987). Trading mechanisms and stock returns: An empirical investigation, Journal of Finance, 62 533-553.] partial adjustment model with noise, we show that opening returns have a tendency towards over-reaction, while closing returns have a tendency towards under-reaction. We suggest that it is these differences that cause a substantial proportion (although not all) of the asymmetric return patterns associated with opening and closing returns. © 2005 Elsevier Inc. All rights reserved.

Feasibility studies of an on-line identification technique

This thesis is concerned with the study of a non-sequential identification technique, so that it may be applied to the identification of process plant mathematical models from process measurements with the greatest degree of accuracy and reliability. In order to study the accuracy of the technique under differing conditions, simple mathematical models were set up on a parallel hybrid. computer and these models identified from input/output measurements by a small on-line digital computer. Initially, the simulated models were identified on-line. However, this method of operation was found not suitable for a thorough study of the technique due to equipment limitations. Further analysis was carried out in a large off-line computer using data generated by the small on-line computer. Hence identification was not strictly on-line. Results of the work have shovm that the identification technique may be successfully applied in practice. An optimum sampling period is suggested, together with noise level limitations for maximum accuracy. A description of a double-effect evaporator is included in this thesis. It is proposed that the next stage in the work will be the identification of a mathematical model of this evaporator using the teclmique described.

Effects of inducer continuity on auditory stream segregation:comparison of physical and perceived continuity in different contexts

The factors influencing the stream segregation of discrete tones and the perceived continuity of discrete tones as continuing through an interrupting masker are well understood as separate phenomena. Two experiments tested whether perceived continuity can influence the build-up of stream segregation by manipulating the perception of continuity during an induction sequence and measuring streaming in a subsequent test sequence comprising three triplets of low and high frequency tones (LHL-…). For experiment 1, a 1.2-s standard induction sequence comprising six 100-ms L-tones strongly promoted segregation, whereas a single extended L-inducer (1.1 s plus 100-ms silence) did not. Segregation was similar to that following the single extended inducer when perceived continuity was evoked by inserting noise bursts between the individual tones. Reported segregation increased when the noise level was reduced such that perceived continuity no longer occurred. Experiment 2 presented a 1.3-s continuous inducer created by bridging the 100-ms silence between an extended L-inducer and the first test-sequence tone. This configuration strongly promoted segregation. Segregation was also increased by filling the silence after the extended inducer with noise, such that it was perceived like a bridging inducer. Like physical continuity, perceived continuity can promote or reduce test-sequence streaming, depending on stimulus context.

Specialist business skills of international students

This paper follows on from that presented at the last BEST conference in Edinburgh (Higson & Hamilton-Jones(2004)). At that stage, the authors outlined their initial research work with students studying on the yearlong International Foundation programmes. at three local FE Colleges allied to Aston University. The research (funded by the University's Teaching Quality Enhancement Funds (TQEF) involved questionnaires and interviews with staff and students (the latter all from overseas). it aimed to identify ways to improve the learning experience of students on the International Foundation programmes, to aid their smooth transition to full degree programmes in Business and Management and to improve the progression rates of such students while studying at Aston. The initial research findings were used to design a module for those students' progress to degree programmes in Aston Business School. This paper discusses how the module was designed, its content and the assessment methods used to help determine whether students are achieving the learning outcomes. The basic principle was to identify areas of study where the International Foundation Programme students needed help in order to improve their learning styles to assist them with the requirements of other modules that they would be studying during their time at Aston. Particular emphasis was put on the need to develop active learners who were not disadvantaged by their lack of awareness of UK culture and society and who were as comfortable performing written work under examination conditions or presenting orally as their UK counterparts. An additional aim was to prepare these students for the placement year which was a compulsory part of their degree. The module, therefore, comprises a range of inputs for a number of staff, a company visit, weekly reflective learning leading to Personal Development Plan (PDP) work, formal examinations, presentations, group work •and individual case studies. This paper also reports on the initial reaction of the students and tutors to the new learning experience with currently 30 participants undertaking the module. Provisional findings suggest that the International Foundation programme has prepared the students well for degree-level work and that as a group of international students they are much more analytical and, after studying the module interactive than their counterparts who have come directly onto Aston degrees. It has shown them still to be quite passive learners, comfortable with facts and lecture-style learning environments, but less comfortable when asked to use their own initiatives. Continuing progress needs to be made in terms of encouraging them to develop a reflective approach to learning with the students taking some time to feel comfortable with an analytical approach to learning. In addition, im account of the students' reactions to having to work through a formal (PDP) and the results of their first assessments will be provided. At Aston, this work is being used as a pilot to recognise good practice with regards to work with further groups of international students. it is hoped that this would have widespread application across the sector.

Educating the iPod generation:undergraduate attitudes, experiences and knowledge of vodcast and podcast use

There is an increasing pressure on university staff to provide ever more information and resources to students. This study investigated student opinions on (audio) podcasts and (video) vodcasts and how well they met requirements and aided learning processes. Two experiments within the Aston University looked at student opinion on, and usage of, podcasts and vodcasts for a selection of their psychology lectures. Recordings were produced first using a hand-held camcorder, and then using the in-house media department. WebCT was used to distribute the podcasts and vodcasts, attitude questionnaires were then circulated at two time points. Overall students indicated that podcasts and vodcasts were a beneficial addition resource for learning, particularly when used in conjunction with lecturers’ slides and as a tool for revision/assessment. The online material translated into students having increased understanding of the material, which supplemented and enhanced their learning without being a substitute for traditional lectures. There is scope for the provision of portable media files to become standard practice within higher education; integrating distance and online learning with traditional approaches to improve teaching and learning.

Sizing energy storage on the 11kV distribution network

The cost and limited flexibility of traditional approaches to 11kV network reinforcement threatens to constrain the uptake of low carbon technologies. Ofgem has released £500m of funding for DNOs to trial innovative techniques and share the learning with the rest of the industry. One of the techniques under study is the addition of Energy Storage at key substations to the network to help with peak load lopping. This paper looks in detail at the sizing algorithm for use in the assessment of alternatives to traditional reinforcement and investigates a method of sizing a battery for use on a Network taking into account load growth, capacity fade and battery lifecycle issues. A further complication to the analysis is the method of operation of the battery system and how this affects the Depth of Discharge (DoD). The proposed method is being trialled on an area of 11kV network in Milton Keynes Central area and the simulation results are presented in this paper.

Practical and cost-effective high-fidelity optical carrier dissemination using coherent communication techniques

We report a unidirectional frequency dissemination scheme for high-fidelity optical carriers deployable over telecommunication networks. For the first time, a 10 Gb/s Binary Phase Shift Keying (BPSK) signal from an ultra-narrow linewidth laser was transmitted through a field-installed optical fibre with round-trip length of 124 km between Cork City and town of Clonakilty, without inline optical amplification. At the receiver, using coherent communication techniques and optical injection-locking the carrier was recovered with noise suppression. The beat signal between the original carrier at the transmitter and recovered carrier at the receiver shows a linewidth of 2.8 kHz. Long term stability measurements revealed fractional instabilities (True Allan deviation) of 3.3 × 10-14 for 1 s averaging time, prior to phase noise cancellation.

Noise, regularizers, and unrealizable scenarios in online learning from restricted training sets

We study the dynamics of on-line learning in multilayer neural networks where training examples are sampled with repetition and where the number of examples scales with the number of network weights. The analysis is carried out using the dynamical replica method aimed at obtaining a closed set of coupled equations for a set of macroscopic variables from which both training and generalization errors can be calculated. We focus on scenarios whereby training examples are corrupted by additive Gaussian output noise and regularizers are introduced to improve the network performance. The dependence of the dynamics on the noise level, with and without regularizers, is examined, as well as that of the asymptotic values obtained for both training and generalization errors. We also demonstrate the ability of the method to approximate the learning dynamics in structurally unrealizable scenarios. The theoretical results show good agreement with those obtained by computer simulations.

Projected sequential Gaussian processes:a C++ tool for interpolation of large datasets with heterogeneous noise

Heterogeneous datasets arise naturally in most applications due to the use of a variety of sensors and measuring platforms. Such datasets can be heterogeneous in terms of the error characteristics and sensor models. Treating such data is most naturally accomplished using a Bayesian or model-based geostatistical approach; however, such methods generally scale rather badly with the size of dataset, and require computationally expensive Monte Carlo based inference. Recently within the machine learning and spatial statistics communities many papers have explored the potential of reduced rank representations of the covariance matrix, often referred to as projected or fixed rank approaches. In such methods the covariance function of the posterior process is represented by a reduced rank approximation which is chosen such that there is minimal information loss. In this paper a sequential Bayesian framework for inference in such projected processes is presented. The observations are considered one at a time which avoids the need for high dimensional integrals typically required in a Bayesian approach. A C++ library, gptk, which is part of the INTAMAP web service, is introduced which implements projected, sequential estimation and adds several novel features. In particular the library includes the ability to use a generic observation operator, or sensor model, to permit data fusion. It is also possible to cope with a range of observation error characteristics, including non-Gaussian observation errors. Inference for the covariance parameters is explored, including the impact of the projected process approximation on likelihood profiles. We illustrate the projected sequential method in application to synthetic and real datasets. Limitations and extensions are discussed. © 2010 Elsevier Ltd.

The dynamics of a genetic algorithm for a simple learning problem

A formalism for describing the dynamics of Genetic Algorithms (GAs) using method s from statistical mechanics is applied to the problem of generalization in a perceptron with binary weights. The dynamics are solved for the case where a new batch of training patterns is presented to each population member each generation, which considerably simplifies the calculation. The theory is shown to agree closely to simulations of a real GA averaged over many runs, accurately predicting the mean best solution found. For weak selection and large problem size the difference equations describing the dynamics can be expressed analytically and we find that the effects of noise due to the finite size of each training batch can be removed by increasing the population size appropriately. If this population resizing is used, one can deduce the most computationally efficient size of training batch each generation. For independent patterns this choice also gives the minimum total number of training patterns used. Although using independent patterns is a very inefficient use of training patterns in general, this work may also prove useful for determining the optimum batch size in the case where patterns are recycled.

The exact sample complexity of PAC-learning problems with unit VC dimension

The Vapnik-Chervonenkis (VC) dimension is a combinatorial measure of a certain class of machine learning problems, which may be used to obtain upper and lower bounds on the number of training examples needed to learn to prescribed levels of accuracy. Most of the known bounds apply to the Probably Approximately Correct (PAC) framework, which is the framework within which we work in this paper. For a learning problem with some known VC dimension, much is known about the order of growth of the sample-size requirement of the problem, as a function of the PAC parameters. The exact value of sample-size requirement is however less well-known, and depends heavily on the particular learning algorithm being used. This is a major obstacle to the practical application of the VC dimension. Hence it is important to know exactly how the sample-size requirement depends on VC dimension, and with that in mind, we describe a general algorithm for learning problems having VC dimension 1. Its sample-size requirement is minimal (as a function of the PAC parameters), and turns out to be the same for all non-trivial learning problems having VC dimension 1. While the method used cannot be naively generalised to higher VC dimension, it suggests that optimal algorithm-dependent bounds may improve substantially on current upper bounds.

Regression with input-dependent noise: A Gaussian process treatment

Gaussian processes provide natural non-parametric prior distributions over regression functions. In this paper we consider regression problems where there is noise on the output, and the variance of the noise depends on the inputs. If we assume that the noise is a smooth function of the inputs, then it is natural to model the noise variance using a second Gaussian process, in addition to the Gaussian process governing the noise-free output value. We show that prior uncertainty about the parameters controlling both processes can be handled and that the posterior distribution of the noise rate can be sampled from using Markov chain Monte Carlo methods. Our results on a synthetic data set give a posterior noise variance that well-approximates the true variance.

Regression with input-dependent noise: A Bayesian treatment

In most treatments of the regression problem it is assumed that the distribution of target data can be described by a deterministic function of the inputs, together with additive Gaussian noise having constant variance. The use of maximum likelihood to train such models then corresponds to the minimization of a sum-of-squares error function. In many applications a more realistic model would allow the noise variance itself to depend on the input variables. However, the use of maximum likelihood to train such models would give highly biased results. In this paper we show how a Bayesian treatment can allow for an input-dependent variance while overcoming the bias of maximum likelihood.