Temporal and Dynamic Analysis

Temporal and dynamic analyses help researchers to better understand why certain

relationships exist and how they change over time (George & Jones, 2000; T. H. Lee,

Gerhart, Weller, Trevor, & Ellig, 2008; Weller, Holtom, Matiaske, & Mellewigt, 2009).

Context Emergent Turnover (CET) theory (Nyberg & Ployhart, 2013) and Event System

theory (EST) (Morgeson et al., 2015) emphasize the importance of temporal and dynamic

analyses in the evaluation of events. EST explains that events are to be understood as

dynamic because as they unfold over time and interact with different components of the

system, their overall strength and effect can change. EST highlights the strength of an

event as a function of its novelty, the level of disruption it causes in the status-quo, and

its criticality. The stronger the event, the longer its effects will last. Likewise, in

evaluating the dynamic, mutual, and co-evolving relationships between different

components of human capital flows, CET theory asserts that “the rate and timing of one

component within the system can be expected to differentially affect outcomes because

other system components react” (Reilly et al., 2014, p. 772).

The aim of the present study is to better understand the effects of staffing events

and contextual factors on work outcomes. We explore the way in which the magnitude of

93 temporal and dynamic effects of staffing events on unit work outcomes. This prevents us

from developing complete formal hypotheses about these effects. However, by taking an

exploratory approach in regards to temporal and dynamic effects of staffing events, we

draw from the existing research to speculate about the way in which the unit response to

staffing events may change over time and how the contextual factors considered in our

study may affect the duration of these effects.

When a staffing event causes a change in the unit’s human capital resources, other

variables in the system are expected to change as well because the unit responds, absorbs

the event’s consequences over time, and adjusts accordingly. Staffing events, unit

turnover rate, and unit performance may influence not only the current state of the

system, but also cause changes to the system in the future. Moreover, depending on the

strength and salience of each of these components and the context in which they take

place, the nature and duration of these effects may differ.

Temporal effects of human capital inflow (hiring). In the discussion

developing hypothesis 1, we explained that the arrival of new hires is expected to initially

cause operational disruptions. This is because new hires and incumbents need time to

adapt to the introduced change to the system. We expect this operational disruption to

disappear gradually as both groups adjust to the new situation and the new ideas and

energy of the newcomers starts to translate into an increase in unit performance. In

evaluation of the temporal changes in the job satisfaction of newcomers, Boswell and her

colleagues (2009) demonstrated that the new hires enjoy an initial increase in job

94 few months (hangover effect). Levels of job satisfaction eventually stabilize around a

year after the arrival of the new employee. Bringing the results of this study up to the unit

level, we expect that the initial operational disruptions, combined with high levels of job

satisfaction among the new hires, will result in a decrease, no effect, or a small increase

in initial unit performance. This depends on which effect (job satisfaction of the

newcomers or the initial operational disruption) is stronger. After the initial period when

both newcomers and incumbents adjust to the new situation, we expect the high levels of

job satisfaction to become more pronounced. Therefore, we anticipate that the initial

period is followed by an increase in job performance. This increase in job performance

fades away or turns negative as the newcomers enter the hangover period. The hangover

effect should gradually disappear as dissatisfied employees leave and the system

stabilizes.

Our expectations about the temporal effects of hiring on turnover are informed by

Jovanovic’s (1979) matching model and Farber’s (1994) empirical evaluation of the

model. These studies showed that newcomers may join the unit without having enough

actual information about whether they are a good fit to the unit or not. Thus, voluntary

turnover rates are low immediately following their arrival because they are still gathering

information about the job. As soon as newcomers realize the reality of their match to the

job and the unit, an increase in voluntary turnover is expected as those who do not

perceive a good fit decide to leave. After this phase is over, a secondary decrease in

voluntary turnover rate is anticipated because those who did not find the unit a good

95

Temporal effects of human capital outflow (dismissal and layoff). As we

discussed in the previous subsections, research strongly supports the notion that human

capital outflow is generally associated with a decrease in unit performance, due to the

operational disruptions and extra work burden added to the workload of the continuing

employees. However, after employees operationally adjust to the change, we anticipate

an increase in unit performance.

Employee dismissal is expected to improve unit performance over time when the

initial adjustment phase after the dismissal of ‘bad apples’ who spoiled the barrel is over.

Therefore, a gradual increase in unit performance and efficiency is predicted. Layoffs are

usually planned to cut the costs associated with human capital and increase the unit

performance.

As discussed in previous subsections, we anticipate a lower rate of voluntary

turnover in the wake of dismissals (H2b) and a higher rate of turnover in response to

layoffs (H3b). We explore the way in which the size and significance of these responses

change over time.

Temporal effects of contextual factors. The relationship between staffing events

and work outcomes is of practical importance to organizations that may be able to

improve some aspects of the workplace context to reduce the negative effects of staffing

events. We expect that positive internal contextual factors (i.e., higher levels of

appreciation ritual participation and collective affective attitude) will shorten the time it

takes for units to adjust to the changes introduced by staffing events. We expect more

96 dynamic analysis, we also explore the way in which the external context of local

unemployment rate influences the size and duration of the effects of staffing events on

work outcomes.

Informed by Reilly et al. (2014), we apply Panel Vector Auto Regression (PVAR)

analysis to explore the temporal relationships in our model. We use the PVAR method to

examine, in addition to the short-term analysis of our hypotheses, the co-evolution and

mutual effects of HR-initiated staffing events, unit performance, and unit turnover rate on

each other, over time and for different levels of contextual factors. As such, we evaluate

whether our short-term hypotheses hold over time, considering mutual changes and

interactions of the variables in the model.

3.3 Methods