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.

The effects of the menstrual cycle on social decision making

The cyclic change in hormonal profiles between the two main phases of the menstrual cycle mediate shifts in mate preference. Males who advertise social dominance are preferred over other men by females in the follicular phase of the cycle. The present study explored assignment of high or low status resources to dominant looking men by females in either phase of the menstrual cycle. Thirteen females who reported that they were free from any kind of hormonal intervention and experienced a 28 day cycle, were invited to participate in a mock job negotiation scenario. Participants were asked to assign either a minimum, low, high or maximum social status job package to a series of male 'employees' that were previously rated to look either dominant or non-dominant. The results showed that during the follicular phase of the cycle participants assigned dominant looking men more high status job resources than the non-dominant looking men. However, during the luteal phase the participants assigned low status resources to the non-dominant looking men. Females are not merely passive observers of male status cues but actively manipulate the environment to assign status. © 2006 Elsevier B.V. All rights reserved.

Optimization of PCB component placements for the collect-and-place machines

This paper presents two hybrid genetic algorithms (HGAs) to optimize the component placement operation for the collect-and-place machines in printed circuit board (PCB) assembly. The component placement problem is to optimize (i) the assignment of components to a movable revolver head or assembly tour, (ii) the sequence of component placements on a stationary PCB in each tour, and (iii) the arrangement of component types to stationary feeders simultaneously. The objective of the problem is to minimize the total traveling time spent by the revolver head for assembling all components on the PCB. The major difference between the HGAs is that the initial solutions are generated randomly in HGA1. The Clarke and Wright saving method, the nearest neighbor heuristic, and the neighborhood frequency heuristic are incorporated into HGA2 for the initialization procedure. A computational study is carried out to compare the algorithms with different population sizes. It is proved that the performance of HGA2 is superior to HGA1 in terms of the total assembly time.

An integrated scheduling problem of PCB components on sequential pick-and-place machines:mathematical models and heuristic solutions

This paper formulates several mathematical models for determining the optimal sequence of component placements and assignment of component types to feeders simultaneously or the integrated scheduling problem for a type of surface mount technology placement machines, called the sequential pick-andplace (PAP) machine. A PAP machine has multiple stationary feeders storing components, a stationary working table holding a printed circuit board (PCB), and a movable placement head to pick up components from feeders and place them to a board. The objective of integrated problem is to minimize the total distance traveled by the placement head. Two integer nonlinear programming models are formulated first. Then, each of them is equivalently converted into an integer linear type. The models for the integrated problem are verified by two commercial packages. In addition, a hybrid genetic algorithm previously developed by the authors is adopted to solve the models. The algorithm not only generates the optimal solutions quickly for small-sized problems, but also outperforms the genetic algorithms developed by other researchers in terms of total traveling distance.

Benevolent sexism at work:gender differences in the distribution of challenging developmental experiences

The current research draws from ambivalent sexism theory to examine potential gender differences in the quantity and quality of developmental work experiences. In a sample of managers in the energy industry, men and women reported participating in a similar number of developmental experiences (with comparable levels of support), but men rated these experiences as more challenging and received more negative feedback than did women. Similarly, a sample of female managers in the health care industry reported comparable amounts, but less challenging types, of developmental experiences than their male counterparts'. The results of three complementary experiments suggest that benevolent sexism is negatively related to men's assignment of challenging experiences to female targets but that men and women were equally likely to express interest in challenging experiences. Taken together, these results suggest that stereotype-based beliefs that women should be protected may limit women's exposure to challenging assignments, which in turn may partially explain the underrepresentation of women at the highest levels of organizations. © The Author(s) 2012.

Metastable de-excitation spectroscopy and density functional theory study of the selective oxidation of crotyl alcohol over Pd(111)

The extremely surface sensitive technique of metastable de-excitation spectroscopy (MDS) has been utilized to probe the bonding and reactivity of crotyl alcohol over Pd(111) and provide insight into the selective oxidation pathway to crotonaldehyde. Auger de-excitation (AD) of metastable He (23S) atoms reveals distinct features associated with the molecular orbitals of the adsorbed alcohol, corresponding to emission from the hydrocarbon skeleton, the O n nonbonding, and C═C π states. The O n and C═C π states of the alcohol are reversed when compared to those of the aldehyde. Density functional theory (DFT) calculations of the alcohol show that an adsorption mode with both C═C and O bonds aligned somewhat parallel to the surface is energetically favored at a substrate temperature below 200 K. Density of states calculations for such configurations are in excellent agreement with experimental MDS measurements. MDS revealed oxidative dehydrogenation of crotyl alcohol to crotonaldehyde between 200 and 250 K, resulting in small peak shifts to higher binding energy. Intramolecular changes lead to the opposite assignment of the first two MOs in the alcohol versus the aldehyde, in accordance with DFT and UPS studies of the free molecules. Subsequent crotonaldehyde decarbonylation and associated propylidyne formation above 260 K could also be identified by MDS and complementary theoretical calculations as the origin of deactivation and selectivity loss. Combining MDS and DFT in this way represents a novel approach to elucidating surface catalyzed reaction pathways associated with a “real-world” practical chemical transformation, namely the selective oxidation of alcohols to aldehydes.

A catalytic reactor for the trapping of free radicals from gas phase oxidation reactions

A catalytic reactor for the trapping of free radicals originating from gas phase catalytic reactions is described and discussed. Radical trapping and identification were initially carried out using a known radical generator such as dicumyl peroxide. The trapping of radicals was further demonstrated by investigating genuine radical oxidation processes, e.g., benzaldehyde oxidation over manganese and cobalt salts. The efficiency of the reactor was finally proven by the partial oxidation of cyclohexane over MoO3, Cr2O3, and WO3, which allowed the identification of all the radical intermediates responsible for the formation of the products cyclohexanol and cyclohexanone. Assignment of the trapped radicals was carried out using spin trapping technique and X -band electron paramagnetic resonance spectroscopy. © 2010 American Institute of Physics.

Assessing an experimental approach to industrial policy evaluation:Applying RCT+ to the case of Creative Credits

Experimental methods of policy evaluation are well-established in social policy and development eco-nomics but are rare in industrial and innovation policy. In this paper, we consider the arguments forapplying experimental methods to industrial policy measures, and propose an experimental policy eval-uation approach (which we call RCT+). This approach combines the randomised assignment of firmsto treatment and control groups with a longitudinal data collection strategy incorporating quantitativeand qualitative data (so-called mixed methods). The RCT+ approach is designed to provide a causativerather than purely summative evaluation, i.e. to assess both ‘whether’ and ‘how’ programme outcomesare achieved. In this paper, we assess the RCT+ approach through an evaluation of Creative Credits – aUK business-to-business innovation voucher initiative intended to promote new innovation partnershipsbetween SMEs and creative service providers. The results suggest the potential value of the RCT+ approachto industrial policy evaluation, and the benefits of mixed methods and longitudinal data collection.

A heuristic approach for component scheduling on a high-speed PCB assembly machine

The collect-and-place machine is one of the most widely used placement machines for assembling electronic components on the printed circuit boards (PCBs). Nevertheless, the number of researches concerning the optimisation of the machine performance is very few. This motivates us to study the component scheduling problem for this type of machine with the objective of minimising the total assembly time. The component scheduling problem is an integration of the component sequencing problem, that is, the sequencing of component placements; and the feeder arrangement problem, that is, the assignment of component types to feeders. To solve the component scheduling problem efficiently, a hybrid genetic algorithm is developed in this paper. A numerical example is used to compare the performance of the algorithm with different component grouping approaches and different population sizes.

A genetic algorithm to optimise the component placement process in the PCB assembly

In printed circuit board (PCB) assembly, the efficiency of the component placement process is dependent on two interrelated issues: the sequence of component placement, that is, the component sequencing problem, and the assignment of component types to feeders of the placement machine, that is, the feeder arrangement problem. In cases where some components with the same type are assigned to more than one feeder, the component retrieval problem should also be considered. Due to their inseparable relationship, a hybrid genetic algorithm is adopted to solve these three problems simultaneously for a type of PCB placement machines called the sequential pick-and-place (PAP) machine in this paper. The objective is to minimise the total distance travelled by the placement head for assembling all components on a PCB. Besides, the algorithm is compared with the methods proposed by other researchers in order to examine its effectiveness and efficiency.

QoE-aware power management in vehicle-to-grid networks:a matching-theoretic approach

Frequency, time and places of charging and discharging have critical impact on the Quality of Experience (QoE) of using Electric Vehicles (EVs). EV charging and discharging scheduling schemes should consider both the QoE of using EV and the load capacity of the power grid. In this paper, we design a traveling plan-aware scheduling scheme for EV charging in driving pattern and a cooperative EV charging and discharging scheme in parking pattern to improve the QoE of using EV and enhance the reliability of the power grid. For traveling planaware scheduling, the assignment of EVs to Charging Stations (CSs) is modeled as a many-to-one matching game and the Stable Matching Algorithm (SMA) is proposed. For cooperative EV charging and discharging in parking pattern, the electricity exchange between charging EVs and discharging EVs in the same parking lot is formulated as a many-to-many matching model with ties, and we develop the Pareto Optimal Matching Algorithm (POMA). Simulation results indicates that the SMA can significantly improve the average system utility for EV charging in driving pattern, and the POMA can increase the amount of electricity offloaded from the grid which is helpful to enhance the reliability of the power grid.

Matching theory based travel plan aware charging algorithms in V2G smart grid networks

The frequency, time and places of charging have large impact on the Quality of Experience (QoE) of EV drivers. It is critical to design effective EV charging scheduling system to improve the QoE of EV drivers. In order to improve EV charging QoE and utilization of CSs, we develop an innovative travel plan aware charging scheduling scheme for moving EVs to be charged at Charging Stations (CS). In the design of the proposed charging scheduling scheme for moving EVs, the travel routes of EVs and the utility of CSs are taken into consideration. The assignment of EVs to CSs is modeled as a two-sided many-to-one matching game with the objective of maximizing the system utility which reflects the satisfactory degrees of EVs and the profits of CSs. A Stable Matching Algorithm (SMA) is proposed to seek stable matching between charging EVs and CSs. Furthermore, an improved Learning based On-LiNe scheduling Algorithm (LONA) is proposed to be executed by each CS in a distributed manner. The performance gain of the average system utility by the SMA is up to 38.2% comparing to the Random Charging Scheduling (RCS) algorithm, and 4.67% comparing to Only utility of Electric Vehicle Concerned (OEVC) scheme. The effectiveness of the proposed SMA and LONA is also demonstrated by simulations in terms of the satisfactory ratio of charging EVs and the the convergence speed of iteration.