Effects of service orientation on job embeddedness in hotel industry

This research aims to develop and analyze a model that depicts work engagement (WE) as a mediator of the relationship between job embeddedness and service orientation. Specifically, the model examines external environmental factors (EEFs) as moderator of the effects of service orientation and job embeddedness in the hospitality industry. All data used for this study were gathered in Iran from hotels frontline employees with a two-weeks’ time lag. These relationships mentioned above were analyzed using AMOS 22.0. It was discovered in the results that WE was indeed a partial mediator and that EEFs indeed moderated the effects of service orientation on job embeddedness with adequate empirical support. The implications of the findings for the managers, the study limitations, and future research recommendations were also discussed.     

How deficiencies in motivation to manage contribute to the United States' competitiveness problem (and what can be done about it)

Data are presented to support the argument that motivation to manage is a major cause of managerial effectiveness, that it declined sharply in the college population during the activism of the 1960s and early 1970s, and that it is now severely lacking in the United States relative to many other countries. Thus America's competitiveness problems appear to be largely motivational in nature. Possible solutions are discussed, including recruiting and selecting for managerial motivation, increasing motivation to manage using training and development techniques, and changing organizational designs (telescoping the scalar chain, moving managerial tasks into non-managerial positions, resorting to professional forms, and expanding venture structures). © 1995 by John Wiley & Sons, Inc.     

Tourism climate insurance: implications and prospects

This paper investigates the intentions of tourists to purchase climate insurance as part of their holiday packages. A research model, based on Bagozzi’s reformulation of attitude theory designed to examine the relationships between climate expectation-disconfirmation and the behavioral intentions of tourists in purchasing tourism climate insurance, with destination loyalty as an outcome. The model hypothesizes and tests whether expectation-disconfirmation can be resolved by insuring the product-climate. A structural equation modeling is utilized. The results reveal that the expectation-disconfirmation of tourists in relation to climate is positively associated with their intentions to purchase insurance and negatively affects loyalty.     

Feedforward versus recurrent neural networks for forecasting monthly japanese yen exchange rates

Neural networks are a relatively new computer artificial intelligence method which attempt to mimic the brain's problem solving process and can be used for predicting nonlinear economic time series. Neural networks are used to look for patterns in data, learn these patterns, and then classify new patterns and make forecasts. Feedforward neural networks pass the data forward from input to output, while recurrent networks have a feedback loop where data can be fed back into the input at some point before it is fed forward again for further processing and final output. Some have argued that since time series data may have autocorrelation or time dependence, the recurrent neural network models which take advantage of time dependence may be useful. Feedforward and recurrent neural networks are used for comparison in forecasting the Japanese yen/US dollar exchange rate. A traditional ARIMA model is used as a benchmark for comparison with the neural network models.Results for out of sample show that the feedforward model is relatively accurate in forecasting both price levels and price direction, despite being quite simple and easy to use. However, the recurrent network forecast performance was lower than that of the feedforward model. This may be because feed forward models must pass the data from back to forward as well as forward to back, and can sometimes become confused or unstable. Both the feedforward and recurrent models performed better than the ARIMA benchmark model.The author wish to thank the reviewers Drs. Kraft and Radford for their helpful comments.     

Neural Networks for Forecasting: An Introduction

Neural networks are nonlinear mapping structures based on the study of the human brain. They have been shown to be universal and highly flexible junction approximators to any data-generating process. Therefore, they are powerful models for forecasting purposes, especially when the underlying data-generating processes are unknown. However, the appropriate design of the network's architecture and learning rules are crucial for obtaining satisfactory results. This study discusses the scope and limitations of neural networks for forecasting problems and provides an example by designing a neural network for forecasting. It is argued that statistical theory can offer some suggestions for designing an optimal network architecture. An example comparing a neural network and ARIM model for forecasting weekly corn prices 1974 through 1993 is provided. Results show the neural network model to be more accurate than the ARIMA.     

Managerial Role Motivation and Role-related Ethical Orientation in Hong Kong

Journal of Business Ethics - Is there a relationship between the psychological construct of hierarchic managerial role motivation and the moral construct of role-related ethical orientation? In...     

Tourism demand: a panel data approach

This paper estimates the coefficients of the determinants of international tourism demand for the period 1995–2014 in the USA using the gravity framework. The analysis is based on a panel dataset of tourist arrivals among 14 countries using autoregressive distributed lag methods. The results show real gross domestic product, consumer price index, real exchange rate and certain specific events have a significant impact on international tourism demand. The income elasticity suggests that tourism is non-luxury goods, and prices and real exchange rate have negative relation to tourist arrivals. We also find that tourism transport infrastructure is a significant determinant of tourist arrivals into USA. This implies that infrastructure to reinforce taste formation is important to attract more international tourists to USA. In addition, results also suggest implications for public and private tourism authorities.     

Motivation to Manage in China: Implications for Strategic HRM

Since 1979, the People's Republic of China (PRC) has made tremendous economic progress. As a result, China and its management practices have received increasing research attention. Human resource management practices in China have been extensively explored elsewhere. Unfortunately, little research has dealt with the concept of hierarchical role motivation theory; its main construct, motivation to manage; and its potential implications for strategic human resource practices in the PRC. The study reported here is an attempt to fill this void.     

Personal characteristics and adjustment of Chinese mainland business expatriates in Hong Kong

Chinese mainland business expatriates assigned to Hong Kong were surveyed assessing their socio-cultural and psychological adjustment. The investigation explored the association of a variety of personal characteristics with adjustment to work and life in the territory. The main results of the study showed that expatriates from the neighbouring Guangdong Province, male expatriates, younger expatriates and expatriates who were accompanied by their spouses were better adjusted in Hong Kong than others. On the other hand, expatriates recruited directly from universities were less well adjusted than those hired from other sources. Implications of these findings are drawn and future avenues for improving and extending this kind of exploratory research are discussed.