Search results

Wonders whether companies actually have employees best interests at heart across physical, mental and spiritual spheres. Posits that most organizations ignore their workforce – not even, in many cases, describing workers as assets! Describes many studies to back up this claim in theis work based on the 2002 Employment Research Unit Annual Conference, in Cardiff, Wales.

Competitiveness is an individual difference variable that incorporates factors generally associated with the desire to excel in comparison to others and the enjoyment of competition. There is still much debate on whether it is helpful or harmful, which may stem from the scattered ways in which it is studied. Thereby, this study aims to properly synthesize the literature concerning the prevailing correlates, underlying theory and frequent applications of competitiveness and to set forth an outline of domains in need of further research and exploration.

The authors do so by using two methods of analysis on a representative sample of 546 peer-reviewed publications.

The authors find that competitiveness research has and will continue to grow expeditiously, but its complexity and cloudiness have not yet been attenuated.

The study uncovers opportunities for pertinent future research on competitiveness to grow more productively and collaboratively by highlighting salient works and identifying the fragmentations that have led the literature into a state of disarray.

Purpose – Time-series regression models are applied to analyse transport safety data for three purposes: (1) to develop a relationship between transport accidents (or incidents) and various time-varying factors, with the aim of identifying the most important factors; (2) to develop a time-series accident model in forecasting future accidents for the given values of future time-varying factors and (3) to evaluate the impact of a system-wide policy, education or engineering intervention on accident counts. Regression models for analysing transport safety data are well established, especially in analysing cross-sectional and panel datasets. There is, however, a dearth of research relating to time-series regression models in the transport safety literature. The purpose of this chapter is to examine existing literature with the aim of identifying time-series regression models that have been employed in safety analysis in relation to wider applications. The aim is to identify time-series regression models that are applicable in analysing disaggregated accident counts.

Methodology/Approach – There are two main issues in modelling time-series accident counts: (1) a flexible approach in addressing serial autocorrelation inherent in time-series processes of accident counts and (2) the fact that the conditional distribution (conditioned on past observations and covariates) of accident counts follow a Poisson-type distribution. Various time-series regression models are explored to identify the models most suitable for analysing disaggregated time-series accident datasets. A recently developed time-series regression model – the generalised linear autoregressive and moving average (GLARMA) – has been identified as the best model to analyse safety data.

Findings – The GLARMA model was applied to a time-series dataset of airproxes (aircraft proximity) that indicate airspace safety in the United Kingdom. The aim was to evaluate the impact of an airspace intervention (i.e., the introduction of reduced vertical separation minima, RVSM) on airspace safety while controlling for other factors, such as air transport movements (ATMs) and seasonality. The results indicate that the GLARMA model is more appropriate than a generalised linear model (e.g., Poisson or Poisson-Gamma), and it has been found that the introduction of RVSM has reduced the airprox events by 15%. In addition, it was found that a 1% increase in ATMs within UK airspace would lead to a 1.83% increase in monthly airproxes in UK airspace.

Practical applications – The methodology developed in this chapter is applicable to many time-series processes of accident counts. The models recommended in this chapter could be used to identify different time-varying factors and to evaluate the effectiveness of various policy and engineering interventions on transport safety or similar data (e.g., crimes).

Originality/value of paper – The GLARMA model has not been properly explored in modelling time-series safety data. This new class of model has been applied to a dataset in evaluating the effectiveness of an intervention. The model recommended in this chapter would greatly benefit researchers and analysts working with time-series data.

In light of the challenge to attract skilled employees in times of dwindling labour supply, the purpose of this paper is to investigate how motivational person-job fit influences the preference for a job. Using a model based on prospect theory, person-job fit is operationalised on three motivational dimensions: extrinsic, enjoyment-based intrinsic, and prosocial intrinsic motivation. Public service motivation (PSM) is theoretically integrated into the model’s dimensions and conceptualised as a fuzzy subset thereof. Within the model, job seekers evaluate their fit with various jobs by comparing their personal motives to the jobs’ motivational incentives, compiling a preference order.

The model was tested using a completely randomised vignette experiment. In all, 102 master’s students had to indicate their preference among various randomly selected job vignettes. Certain vignettes presented to experimental group (EG) subjects were individually manipulated to provide either very good or very poor person-job fit. The manipulation’s effect on vignette preference was analysed using logistic regression.

EG subjects significantly preferred both well-fitting and random vignettes over misfitting ones. No significant preference was found comparing well-fitting and random vignettes. Coherent with prospect theory, the deterring effect of misfit appears to be stronger than the attraction effect of good fit, supporting the model.

Most previous research on motivational person-job fit focused on a single factor (e.g. PSM) when predicting job preference. This study, in contrast, incorporates multiple motivational dimensions, capturing that individuals usually pursue mixed motives.

A range of organizational culture scales have been developed and applied in various industries. However, the measurement of organizational culture is noticeably different according to industry. Measuring organizational culture, specifically as it relates to the hospitality industry, is also a research area that has remained relatively unexplored. The purpose of this chapter is to discuss some essential problems and gaps existing in the previous studies. This chapter also presents a new scale entitled the “hospitality industry organization culture scale” that applies specifically to the hospitality context, and contributes to our understanding of organizational culture within this context. A multidisciplinary and mixed-method research approaches were followed in order to develop a new organizational culture scale for the hospitality industry. The findings suggest that the hospitality industry has unique cultural characteristics that are distinguished from similar industries.

Muslimophobia, or prejudice toward Muslims, results in employment discrimination, social exclusion of Muslims, anti-Muslim hate crimes, and physical and verbal assaults, in the United States and globally. Moreover, anti-Muslim incidents are on the rise in many countries. In this chapter, we provide a review of Muslimophobia and its dynamics and consequences in the workplace. We also make suggestions for reducing prejudice toward Muslim employees, using social psychological perspectives, particularly intergroup contact theory, and research on prejudice reduction. It is also argued that leaders play an important role in the combating of Muslimophobia, including creating opportunities for personalized interactions with Muslim employees and disseminating more information about Muslims and Islam. This chapter concludes with practical implications and suggestions for future research directions. Although there is much work to be done in reducing Muslimophobia and discrimination against Muslims, social psychological research emanating from intergroup contact theory suggests that it is a viable path for researchers and practitioners to pursue.