Work-Unit Absenteeism: Effects of Satisfaction, Commitment, Labor Market Conditions, and Time

Prior research is limited in explaining absenteeism at the unit level and over time. We developed and tested a model of unit-level absenteeism using five waves of data collected over six years from 115 work units in a large state agency. Unit-level job satisfaction, organizational commitment, and local unemployment were modeled as time-varying predictors of absenteeism. Shared satisfaction and commitment interacted in predicting absenteeism but were not related to the rate of change in absenteeism over time. Unit-level satisfaction and commitment were more strongly related to absenteeism when units were located in areas with plentiful job alternatives

Learning to Communicate: A Machine Learning Framework for Heterogeneous Multi-Agent Robotic Systems

We present a machine learning framework for multi-agent systems to learn both the optimal policy for maximizing the rewards and the encoding of the high dimensional visual observation. The encoding is useful for sharing local visual observations with other agents under communication resource constraints. The actor-encoder encodes the raw images and chooses an action based on local observations and messages sent by the other agents. The machine learning agent generates not only an actuator command to the physical device, but also a communication message to the other agents. We formulate a reinforcement learning problem, which extends the action space to consider the communication action as well. The feasibility of the reinforcement learning framework is demonstrated using a 3D simulation environment with two collaborating agents. The environment provides realistic visual observations to be used and shared between the two agents.Comment: AIAA SciTech 201

What’s past (and present) is prologue : interactions between justice levels and trajectories predicting behavioral reciprocity

Much of organizational justice research has tended to take a static approach, linking employees’ contemporaneous justice levels to outcomes of interest. In the present study, we tested a dynamic model emphasizing the interactive influences of both justice levels and trajectories for predicting behavioral social exchange outcomes. Specifically, our model posited both main effects and interactions between present justice levels and past justice changes over time in predicting helping behavior and voluntary turnover behavior. Data over four yearly measurement periods from 4,348 employees of a banking organization generally supported the notion that justice trajectories interact with absolute levels to predict both outcomes. Together, the findings highlight how employees invoke present fairness evaluations within the context of past fairness trends—rather than either in isolation—to inform decisions about behaviorally reciprocating at work

Applicant perspectives during selection

We provide a comprehensive but critical review of research on applicant reactions to selection procedures published since 2000 (n = 145), when the last major review article on applicant reactions appeared in the Journal of Management. We start by addressing the main criticisms levied against the field to determine whether applicant reactions matter to individuals and employers (“So what?”). This is followed by a consideration of “What’s new?” by conducting a comprehensive and detailed review of applicant reaction research centered upon four areas of growth: expansion of the theoretical lens, incorporation of new technology in the selection arena, internationalization of applicant reactions research, and emerging boundary conditions. Our final section focuses on “Where to next?” and offers an updated and integrated conceptual model of applicant reactions, four key challenges, and eight specific future research questions. Our conclusion is that the field demonstrates stronger research designs, with studies incorporating greater control, broader constructs, and multiple time points. There is also solid evidence that applicant reactions have significant and meaningful effects on attitudes, intentions, and behaviors. At the same time, we identify some remaining gaps in the literature and a number of critical questions that remain to be explored, particularly in light of technological and societal changes

The impact of preparatory activities on medical school selection outcomes: a cross-sectional survey of applicants to the University of Adelaide Medical School in 2007

Background: Selection into medical school is highly competitive with more applicants than places. Little is known about the preparation that applicants undertake for this high stakes process. The study aims to determine what preparatory activities applicants undertake and what difficulties they encounter for each stage of the application process to medical school and in particular what impact these have on the outcome. Methods: A cross-sectional survey of 1097 applicants who applied for a place in the University of Adelaide Medical School in 2007 and participated in the UMAT (Undergraduate Medicine and Health Sciences Admission Test) and oral assessment components of the selection process. The main outcome measures were an offer of an interview and offer of a place in the medical school and were analysed using logistic regression. Results: The odds of a successful outcome increased with each additional preparatory activity undertaken for the UMAT (odds ratio 1.22, 95% confidence interval 1.11 to 1.33; P < 0.001) and the oral assessment (1.36, 1.19 to 1.55; P < 0.001) stage of selection. The UMAT preparatory activities associated with the offer of an interview were attendance of a training course by a private organisation (1.75, 1.35 to 2.27: P < 0.001), use of online services of a private organisation (1.58, 1.23 to 2.04; P < 0.001), and familiarising oneself with the process (1.52, 1.15 to 2.00; p = 0.021). The oral assessment activities associated with an offer of a place included refining and learning a personal resume (9.73, 2.97 to 31.88; P < 0.001) and learning about the course structure (2.05, 1.29 to 3.26; P = 0.022). For the UMAT, applicants who found difficulties with learning for this type of test (0.47, 0.35 to 0.63: P < 0.001), with the timing of UMAT in terms of school exams (0.48, 0.5 to 0.66; P < 0.001) and with the inability to convey personal skills with the UMAT (0.67, 0.52 to 0.86; P = 0.026) were significantly less likely to be offered an interview. Conclusions: Medical schools make an enormous effort to undertake a selection process that is fair and equitable and which selects students most appropriate for medical school and the course they provide. Our results indicate that performance in the selection processes can be improved by training. However, if these preparatory activities may be limited to those who can access them, the playing field is not even and increasing equity of access to medical schools will not be achieved.Caroline O Laurence, Ian T Zajac, Michelle Lorimer, Deborah A Turnbull and Karen E Sumne