The effects of perceived quality of organizationally provided meal service on employees’ job performance and mediating role of organizational identification

Contemporary managers are developing alternative ways to sustain their competitive advantages. Motivation-enhancing features such as high-quality meal service provided by organizations can be thought of as one of these methods. The effect of the perceived quality of meal service provided by organizations on the job performance of employees and the mediating role of organizational identification during this process is studied. Private security-sector employees working in Turkey (N?=?597) are being focused in this study. As a result of analyses (correlation and regression analyses, structural equation model), the authors find that the perceived quality of meal service provided by organizations improves employees’ job performance significantly and organizational identification has a partial mediating role on this association. The findings of this study will be of interest to key stakeholders such as public or private organizations, labor unions and the media.     

Burnout,coping and suicidal ideation: An application and extension of the job demand-control-support model

Suicidal tendencies are typically considered related to individual traits or predispositions, but some occupations have significantly higher rates than other occupations and the general population. This article proposes that stressful work conditions may be important in understanding occupational variations in suicidal tendencies. It explores the links between work-related factors and burnout, and suicidal thoughts among veterinarians. Burnout appears to be an important mediator in understanding veterinarians’ suicidal tendencies; work conditions that are emotionally exhausting for veterinarians may foster suicidal thoughts. Individual coping strategies are also explored. Emotion-focused strategies of avoidance and alcohol consumption not only exacerbate burnout and suicidal thoughts but also amplify the harmful effects of some job demands. Active problem solving is not as beneficial as expected, but a supportive work environment is a valuable coping resource. Organizational interventions and coping resources effective in reducing burnout may also reduce the risk of suicide for those in service occupations.     

Investment model predictions of workplace ostracism on K–12 teachers’ commitment to their schools and the profession of teaching

The purpose of this study was to determine how the ostracism of K-12 teachers influences their commitment to their schools and commitment to the teaching profession. The investment model was used to situate ostracism as a predictor of teacher commitment. Participants were 200 full-time K-12 teachers who completed a survey assessing their experiences with ostracism at work and investment model variables (i.e., investments, quality of alternatives, satisfaction, and commitment). Results confirmed investment model predictions with teachers’ investments, quality of alternatives, and satisfaction predicting their commitment to their schools and profession. Results of mediation models also demonstrated that controlling for teachers’ investments and quality of alternatives, ostracism predicted commitment indirectly through its effect on satisfaction. This study revealed that teacher commitment is explained by investment model predictions, but after controlling for those predictions, is further explained by ostracism from teacher colleagues.     

Approximate confidence intervals for the weighted kappa coefficient of a binary diagnostic test subject to a case–control design

Case–control design to assess the accuracy of a binary diagnostic test (BDT) is very frequent in clinical practice. This design consists of applying the diagnostic test to all of the individuals in a sample of those who have the disease and in another sample of those who do not have the disease. The sensitivity of the diagnostic test is estimated from the case sample and the specificity is estimated from the control sample. Another parameter which is used to assess the performance of a BDT is the weighted kappa coefficient. The weighted kappa coefficient depends on the sensitivity and specificity of the diagnostic test, on the disease prevalence and on the weighting index. In this article, confidence intervals are studied for the weighted kappa coefficient subject to a case–control design and a method is proposed to calculate the sample sizes to estimate this parameter. The results obtained were applied to a real example.     

New V control chart for the Maxwell distribution

Control charts have been popularly used as a user-friendly yet technically sophisticated tool to monitor whether a process is in statistical control or not. These charts are basically constructed under the normality assumption. But in many practical situations in real life this normality assumption may be violated. One such non-normal situation is to monitor the process variability from a skewed parent distribution where we propose the use of a Maxwell control chart. We introduce a pivotal quantity for the scale parameter of the Maxwell distribution which follows a gamma distribution. Probability limits and L-sigma limits are studied along with performance measure based on average run length and power curve. To avoid the complexity of future calculations for practitioners, factors for constructing control chart for monitoring the Maxwell parameter are given for different sample sizes and for different false alarm rate. We also provide simulated data to illustrate the Maxwell control chart. Finally, a real life example has been given to show the importance of such a control chart.     

Statistical measurement of the inventory shortage cost

In searching for the optimal inventory control policy, the objective is to minimize the expected total costs related, of which the shortage cost is an important element. Due to the difficulty in calculating the indirect cost of the loss of goodwill resulted from the shortage, practitioners and researchers often simply assume a fixed penalty cost on the inventory shortage or switch to the alternative method by assigning a specific customer service level. The development of an appropriate tool for measuring the shortage cost can help a business control the total costs and improve the productivity more effectively. This paper proposes probabilistic measurements of the shortage cost, based on mathematical relationship between the cost and the shortage amount. The derived closed-form estimates of the expected shortage cost value can then be applied to support the determination of the optimal inventory control policy.     

Optimal design of the adaptive exponentially weighted moving average control chart over a range of mean shifts

The adaptive exponentially weighted moving average (AEWMA) control chart is a smooth combination of the Shewhart and exponentially weighted moving average (EWMA) control charts. This chart was proposed by Cappizzi and Masarotto (2003) to achieve a reasonable performance for both small and large shifts. Cappizzi and Masarotto (2003) used a pair of shifts in designing their control chart. In this study, however, the process mean shift is considered as a random variable with a certain probability distribution and the AEWMA control chart is optimized for a wide range of mean shifts according to that probability distribution and not just for a pair of shifts. Using the Markov chain technique, the results show that the new optimization design can improve the performance of the AEWMA control chart from an overall point of view relative to the various designs presented by Cappizzi and Masarotto (2003). Optimal design parameters that achieve the desired in-control average run length (ARL) are computed in several cases and formulas used to find approximately their values are given. Using these formulas, the practitioner can compute the optimal design parameters corresponding to any desired in-control ARL without the need to apply the optimization procedure. The results obtained by these formulas are very promising and would particularly facilitate the design of the AEWMA control chart for any in-control ARL value.     

On robustness of the Shiryaev–Roberts change-point detection procedure under parameter misspecification in the post-change distribution

The gist of the quickest change-point detection problem is to detect the presence of a change in the statistical behavior of a series of sequentially made observations, and do so in an optimal detection-speed-versus-“false-positive”-risk manner. When optimality is understood either in the generalized Bayesian sense or as defined in Shiryaev's multi-cyclic setup, the so-called Shiryaev–Roberts (SR) detection procedure is known to be the “best one can do”, provided, however, that the observations’ pre- and post-change distributions are both fully specified. We consider a more realistic setup, viz. one where the post-change distribution is assumed known only up to a parameter, so that the latter may be misspecified. The question of interest is the sensitivity (or robustness) of the otherwise “best” SR procedure with respect to a possible misspecification of the post-change distribution parameter. To answer this question, we provide a case study where, in a specific Gaussian scenario, we allow the SR procedure to be “out of tune” in the way of the post-change distribution parameter, and numerically assess the effect of the “mistuning” on Shiryaev's (multi-cyclic) Stationary Average Detection Delay delivered by the SR procedure. The comprehensive quantitative robustness characterization of the SR procedure obtained in the study can be used to develop the respective theory as well as to provide a rational for practical design of the SR procedure. The overall qualitative conclusion of the study is an expected one: the SR procedure is less (more) robust for less (more) contrast changes and for lower (higher) levels of the false alarm risk.     

Monotonic change point estimation of generalized linear model-based regression profiles

In this article, a maximum likelihood estimator is derived in the generalized linear model-based regression profiles under monotonic change in Phase II. The performance of the proposed estimator is comprehensively investigated through some special cases, and compared with estimators under step change and drift. The results show that the proposed estimator has better performance in small and medium shifts under different increasing changes. Finally, the applicability of the proposed estimator is illustrated using a real case.